Source Code for Module test_suite.system_tests.relax_disp

   1  ############################################################################### 
   2  #                                                                             # 
   3  # Copyright (C) 2006-2015 Edward d'Auvergne                                   # 
   4  # Copyright (C) 2009 Sebastien Morin                                          # 
   5  # Copyright (C) 2013-2014 Troels E. Linnet                                    # 
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   7  # This file is part of the program relax (http://www.nmr-relax.com).          # 
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  23   
  24  # Python module imports. 
  25  from os import F_OK, access, getcwd, path, sep 
  26  import copy 
  27  from numpy import array, asarray, average, exp, median, inf, linspace, log, std, sum, zeros 
  28  from minfx.generic import generic_minimise 
  29  from random import gauss 
  30  import re, math 
  31  from tempfile import mkdtemp, NamedTemporaryFile 
  32   
  33   
  34  # relax module imports. 
  35  from auto_analyses import relax_disp 
  36  from auto_analyses.relax_disp_repeat_cpmg import DIC_KEY_FORMAT, Relax_disp_rep 
  37  from data_store import Relax_data_store; ds = Relax_data_store() 
  38  import dep_check 
  39  from lib.dispersion.variables import EXP_TYPE_CPMG_DQ, EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST, EXP_TYPE_R1RHO, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LIST_FULL, MODEL_LM63, MODEL_M61B, MODEL_MP05, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_R1RHO_2SITE, MODEL_PARAMS, MODEL_R2EFF, MODEL_TP02, MODEL_TAP03 
  40  from lib.errors import RelaxError 
  41  from lib.io import extract_data, get_file_path 
  42  from lib.spectrum.nmrpipe import show_apod_extract, show_apod_rmsd, show_apod_rmsd_dir_to_files, show_apod_rmsd_to_file 
  43  from pipe_control.mol_res_spin import generate_spin_string, return_spin, spin_loop 
  44  from pipe_control.minimise import assemble_scaling_matrix 
  45  from specific_analyses.relax_disp.checks import check_missing_r1 
  46  from specific_analyses.relax_disp.estimate_r2eff import estimate_r2eff 
  47  from specific_analyses.relax_disp.data import average_intensity, check_intensity_errors, generate_r20_key, get_curve_type, has_exponential_exp_type, loop_exp_frq, loop_exp_frq_offset_point, loop_time, return_grace_file_name_ini, return_param_key_from_data, spin_ids_to_containers 
  48  from specific_analyses.relax_disp.data import INTERPOLATE_DISP, INTERPOLATE_OFFSET, X_AXIS_DISP, X_AXIS_W_EFF, X_AXIS_THETA, Y_AXIS_R2_R1RHO, Y_AXIS_R2_EFF 
  49  from specific_analyses.relax_disp.model import models_info, nesting_param 
  50  from specific_analyses.relax_disp.parameters import linear_constraints 
  51  from status import Status; status = Status() 
  52  from target_functions.relax_fit_wrapper import Relax_fit_opt 
  53  from test_suite.system_tests.base_classes import SystemTestCase 
  54   
  55   
  56 -class Relax_disp(SystemTestCase): 
  57      """Class for testing various aspects specific to relaxation dispersion curve-fitting.""" 
  58   
  59 -    def __init__(self, methodName='runTest'): 
  60          """Skip certain tests if the C modules are non-functional. 
  61   
  62          @keyword methodName:    The name of the test. 
  63          @type methodName:       str 
  64          """ 
  65   
  66          # Execute the base class method. 
  67          super(Relax_disp, self).__init__(methodName) 
  68   
  69          # Tests to skip. 
  70          blacklist = [ 
  71              'test_m61b_data_to_m61b' 
  72          ] 
  73          if methodName in blacklist: 
  74              status.skipped_tests.append([methodName, None, self._skip_type]) 
  75   
  76          # Missing module. 
  77          if not dep_check.C_module_exp_fn: 
  78              # The list of tests to skip. 
  79              to_skip = [ 
  80                  "test_bug_atul_srivastava", 
  81                  "test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp", 
  82                  "test_bug_9999_slow_r1rho_r2eff_error_with_mc", 
  83                  "test_estimate_r2eff_err", 
  84                  "test_estimate_r2eff_err_auto", 
  85                  "test_estimate_r2eff_err_methods", 
  86                  "test_finite_value", 
  87                  "test_exp_fit", 
  88                  "test_m61_exp_data_to_m61", 
  89                  "test_r1rho_kjaergaard_auto", 
  90                  "test_r1rho_kjaergaard_auto_check_graphs", 
  91                  "test_r1rho_kjaergaard_man", 
  92                  "test_r1rho_kjaergaard_missing_r1", 
  93                  "test_value_write_calc_rotating_frame_params_auto_analysis" 
  94              ] 
  95   
  96              # Store in the status object. 
  97              if methodName in to_skip: 
  98                  status.skipped_tests.append([methodName, 'Relax curve-fitting C module', self._skip_type]) 
  99   
 100          # If not scipy.optimize.leastsq. 
 101          if not dep_check.scipy_module: 
 102              # The list of tests to skip. 
 103              to_skip = [ 
 104                  "test_estimate_r2eff_err_methods" 
 105              ] 
 106   
 107              # Store in the status object. 
 108              if methodName in to_skip: 
 109                  status.skipped_tests.append([methodName, 'scipy.optimize.leastsq module', self._skip_type]) 
 110   
 111          # If not NMRPipe showApod program in PATH. 
 112          if not dep_check.showApod_software: 
 113              # The list of tests to skip. 
 114              to_skip = [ 
 115                  "test_show_apod_extract", 
 116                  "test_show_apod_rmsd", 
 117                  "test_show_apod_rmsd_to_file", 
 118                  "test_show_apod_rmsd_dir_to_files" 
 119              ] 
 120   
 121              # Store in the status object. 
 122              if methodName in to_skip: 
 123                  status.skipped_tests.append([methodName, 'NMRPipe showApod program', self._skip_type]) 
 124   
 125          # If not matplotlib module 
 126          if not dep_check.matplotlib_module: 
 127              # The list of tests to skip. 
 128              to_skip = [ 
 129                  "test_repeat_cpmg" 
 130              ] 
 131   
 132              # Store in the status object. 
 133              if methodName in to_skip: 
 134                  status.skipped_tests.append([methodName, 'matplotlib module', self._skip_type]) 
 135   
 136   
 137 -    def setUp(self): 
 138          """Set up for all the functional tests.""" 
 139   
 140          # Create the data pipe. 
 141          self.interpreter.pipe.create('relax_disp', 'relax_disp') 
 142   
 143          # Create a temporary directory for dumping files. 
 144          ds.tmpdir = mkdtemp() 
 145          self.tmpdir = ds.tmpdir 
 146   
 147   
 148 -    def setup_bug_22146_unpacking_r2a_r2b_cluster(self, folder=None, model_analyse=None, places = 7): 
 149          """Setup data for the catch of U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered full dispersion models. 
 150   
 151          @keyword folder:            The name of the folder for the test data. 
 152          @type folder:               str 
 153          @keyword model_analyse:     The name of the model which will be tested. 
 154          @type model_analyse:        str 
 155          """ 
 156   
 157          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 158   
 159          # Data. 
 160          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22146_unpacking_r2a_r2b_cluster'+sep+folder 
 161   
 162          ## Experiments 
 163          # Exp 1 
 164          sfrq_1 = 500.0*1E6 
 165          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
 166          time_T2_1 = 0.05 
 167          ncycs_1 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 50] 
 168          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 169          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 170          r2eff_errs_1 = [0.0] * len(ncycs_1) 
 171          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
 172   
 173          sfrq_2 = 600.0*1E6 
 174          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
 175          time_T2_2 = 0.06 
 176          ncycs_2 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 60] 
 177          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 178          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 179          r2eff_errs_2 = [0.0] * len(ncycs_2) 
 180          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
 181   
 182          sfrq_3 = 700.0*1E6 
 183          r20_key_3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_3) 
 184          time_T2_3 = 0.07 
 185          ncycs_3 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 50, 70] 
 186          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 187          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 188          r2eff_errs_3 = [0.0] * len(ncycs_3) 
 189          exp_3 = [sfrq_3, time_T2_3, ncycs_3, r2eff_errs_3] 
 190   
 191          # Collect all exps 
 192          exps = [exp_1, exp_2, exp_3] 
 193   
 194          R20 = [5.1, 5.2, 5.3, 10.1, 10.2, 10.3, 6.1, 6.2, 6.3, 11.1, 11.2, 11.3, 7.1, 7.2, 7.3, 12.1, 12.2, 12.3, 8.1, 8.2, 8.3, 13.1, 13.2, 13.3] 
 195          dw_arr = [1.0, 2.0, 3.0, 4.0] 
 196          pA_arr = [0.9] 
 197          kex_arr = [1000.] 
 198   
 199          spins = [ 
 200                  ['Ala', 1, 'N', {'r2a': {r20_key_1: R20[0], r20_key_2: R20[1], r20_key_3: R20[2]}, 'r2b': {r20_key_1: R20[3], r20_key_2: R20[4], r20_key_3: R20[5]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[0]}], 
 201                  ['Ala', 2, 'N', {'r2a': {r20_key_1: R20[6], r20_key_2: R20[7], r20_key_3: R20[8]}, 'r2b': {r20_key_1: R20[9], r20_key_2: R20[10], r20_key_3: R20[11]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[1]}], 
 202                  ['Ala', 3, 'N', {'r2a': {r20_key_1: R20[12], r20_key_2: R20[13], r20_key_3: R20[14]}, 'r2b': {r20_key_1: R20[15], r20_key_2: R20[16], r20_key_3: R20[17]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[2]}], 
 203                  ['Ala', 4, 'N', {'r2a': {r20_key_1: R20[18], r20_key_2: R20[19], r20_key_3: R20[20]}, 'r2b': {r20_key_1: R20[21], r20_key_2: R20[22], r20_key_3: R20[23]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[3]}], 
 204                  ] 
 205   
 206          # Create the data pipe. 
 207          pipe_name = 'base pipe' 
 208          pipe_type = 'relax_disp' 
 209          pipe_bundle = 'relax_disp' 
 210          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type, bundle = pipe_bundle) 
 211   
 212          # Generate the sequence. 
 213          for res_name, res_num, spin_name, params in spins: 
 214              self.interpreter.spin.create(res_name=res_name, res_num=res_num, spin_name=spin_name) 
 215   
 216          # Set isotope 
 217          self.interpreter.spin.isotope('15N', spin_id='@N') 
 218   
 219          # Now loop over the experiments, to set the variables in relax. 
 220          exp_ids = [] 
 221          for exp_i in exps: 
 222              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 223              exp_id = 'CPMG_%3.1f' % (sfrq/1E6) 
 224              exp_ids.append(exp_id) 
 225   
 226              ids = [] 
 227              for ncyc in ncycs: 
 228                  nu_cpmg = ncyc / time_T2 
 229                  cur_id = '%s_%.1f' % (exp_id, nu_cpmg) 
 230                  ids.append(cur_id) 
 231   
 232                  # Set the spectrometer frequency. 
 233                  self.interpreter.spectrometer.frequency(id=cur_id, frq=sfrq) 
 234   
 235                  # Set the experiment type. 
 236                  self.interpreter.relax_disp.exp_type(spectrum_id=cur_id, exp_type=EXP_TYPE_CPMG_SQ) 
 237   
 238                  # Set the relaxation dispersion CPMG constant time delay T (in s). 
 239                  self.interpreter.relax_disp.relax_time(spectrum_id=cur_id, time=time_T2) 
 240   
 241                  # Set the relaxation dispersion CPMG frequencies. 
 242                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=cur_id, cpmg_frq=nu_cpmg) 
 243   
 244          print("\n\nThe experiment IDs are %s." % cdp.spectrum_ids) 
 245   
 246          ### Now do fitting. 
 247          # Change pipe. 
 248   
 249          pipe_name_MODEL = "%s_%s"%(pipe_name, model_analyse) 
 250          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_MODEL, bundle_to = pipe_bundle) 
 251          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 252   
 253          # Now read data in. 
 254          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
 255              exp_id = exp_ids[mi] 
 256              exp_i = exps[mi] 
 257              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 258   
 259              # Then loop over the spins. 
 260              for res_name, res_num, spin_name, params in spins: 
 261                  cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 262   
 263                  # Define file name 
 264                  file_name = "%s%s.txt" % (exp_id, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
 265   
 266                  # Read in the R2eff file to put into spin structure. 
 267                  self.interpreter.relax_disp.r2eff_read_spin(id=exp_id, spin_id=cur_spin_id, file=file_name, dir=data_path, disp_point_col=1, data_col=2, error_col=3) 
 268   
 269          # Then select model. 
 270          self.interpreter.relax_disp.select_model(model=model_analyse) 
 271   
 272          # Then cluster 
 273          self.interpreter.relax_disp.cluster('model_cluster', ":1-100") 
 274   
 275          # Grid search 
 276          low_arr = R20 + dw_arr + pA_arr + kex_arr 
 277          self.interpreter.minimise.grid_search(lower=low_arr, upper=low_arr, inc=1, constraints=True, verbosity=1) 
 278   
 279          # Then loop over the defined spins and read the parameters. 
 280          for i in range(len(spins)): 
 281              res_name, res_num, spin_name, params = spins[i] 
 282              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 283              cur_spin = return_spin(cur_spin_id) 
 284   
 285              for mo_param in cur_spin.params: 
 286                  print(mo_param) 
 287                  # The R2 is a dictionary, depending on spectrometer frequency. 
 288                  if isinstance(getattr(cur_spin, mo_param), dict): 
 289                      for key, val in list(getattr(cur_spin, mo_param).items()): 
 290                          should_be = params[mo_param][key] 
 291                          print(cur_spin.model, res_name, cur_spin_id, mo_param, key, float(val), should_be) 
 292                          self.assertAlmostEqual(val, should_be) 
 293                  else: 
 294                      should_be = float(params[mo_param]) 
 295                      val = getattr(cur_spin, mo_param) 
 296                      print(cur_spin.model, res_name, cur_spin_id, mo_param, val, should_be) 
 297                      self.assertAlmostEqual(val, should_be) 
 298   
 299              # Test chi2. 
 300              # At this point the chi-squared value at the solution should be zero, as the relaxation data was created with the same parameter values. 
 301              self.assertAlmostEqual(cur_spin.chi2, 0.0, places = places) 
 302   
 303   
 304 -    def setup_r1rho_kjaergaard(self, cluster_ids=[], read_R1=True): 
 305          """Set up the data for the test_r1rho_kjaergaard_*() system tests.""" 
 306   
 307          # The path to the data files. 
 308          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 309   
 310          # Set pipe name, bundle and type. 
 311          ds.pipe_name = 'base pipe' 
 312          ds.pipe_bundle = 'relax_disp' 
 313          ds.pipe_type = 'relax_disp' 
 314   
 315          # Create the data pipe. 
 316          self.interpreter.pipe.create(pipe_name=ds.pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type) 
 317   
 318          # Read the spins. 
 319          self.interpreter.spectrum.read_spins(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 320   
 321          # Name the isotope for field strength scaling. 
 322          self.interpreter.spin.isotope(isotope='15N') 
 323   
 324          # Set number of experiments to be used. 
 325          NR_exp = 70 
 326   
 327          # Load the experiments settings file. 
 328          expfile = open(data_path+sep+'exp_parameters_sort.txt', 'r') 
 329          expfileslines = expfile.readlines()[:NR_exp] 
 330          expfile.close() 
 331   
 332          # In MHz 
 333          yOBS = 81.050 
 334          # In ppm 
 335          yCAR = 118.078 
 336          centerPPM_N15 = yCAR 
 337   
 338          ## Read the chemical shift data. 
 339          self.interpreter.chemical_shift.read(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 340   
 341          # The lock power to field, has been found in an calibration experiment. 
 342          spin_lock_field_strengths_Hz = {'35': 431.0, '39': 651.2, '41': 800.5, '43': 984.0, '46': 1341.11, '48': 1648.5} 
 343   
 344          # Apply spectra settings. 
 345          # Count settings 
 346          j = 0 
 347          for i in range(len(expfileslines)): 
 348              line = expfileslines[i] 
 349              if line[0] == "#": 
 350                  continue 
 351              else: 
 352                  # DIRN I deltadof2 dpwr2slock ncyc trim ss sfrq 
 353                  DIRN = line.split()[0] 
 354                  I = int(line.split()[1]) 
 355                  deltadof2 = line.split()[2] 
 356                  dpwr2slock = line.split()[3] 
 357                  ncyc = int(line.split()[4]) 
 358                  trim = float(line.split()[5]) 
 359                  ss = int(line.split()[6]) 
 360                  set_sfrq = float(line.split()[7]) 
 361                  apod_rmsd = float(line.split()[8]) 
 362                  spin_lock_field_strength = spin_lock_field_strengths_Hz[dpwr2slock] 
 363   
 364                  # Calculate spin_lock time 
 365                  time_sl = 2*ncyc*trim 
 366   
 367                  # Define file name for peak list. 
 368                  FNAME = "%s_%s_%s_%s_max_standard.ser"%(I, deltadof2, dpwr2slock, ncyc) 
 369                  sp_id = "%s_%s_%s_%s"%(I, deltadof2, dpwr2slock, ncyc) 
 370   
 371                  # Load the peak intensities. 
 372                  self.interpreter.spectrum.read_intensities(file=FNAME, dir=data_path+sep+'peak_lists', spectrum_id=sp_id, int_method='height') 
 373   
 374                  # Set the peak intensity errors, as defined as the baseplane RMSD. 
 375                  self.interpreter.spectrum.baseplane_rmsd(error=apod_rmsd, spectrum_id=sp_id) 
 376   
 377                  # Set the relaxation dispersion experiment type. 
 378                  self.interpreter.relax_disp.exp_type(spectrum_id=sp_id, exp_type='R1rho') 
 379   
 380                  # Set The spin-lock field strength, nu1, in Hz 
 381                  self.interpreter.relax_disp.spin_lock_field(spectrum_id=sp_id, field=spin_lock_field_strength) 
 382   
 383                  # Calculating the spin-lock offset in ppm, from offsets values provided in Hz. 
 384                  frq_N15_Hz = yOBS * 1E6 
 385                  offset_ppm_N15 = float(deltadof2) / frq_N15_Hz * 1E6 
 386                  omega_rf_ppm = centerPPM_N15 + offset_ppm_N15 
 387   
 388                  # Set The spin-lock offset, omega_rf, in ppm. 
 389                  self.interpreter.relax_disp.spin_lock_offset(spectrum_id=sp_id, offset=omega_rf_ppm) 
 390   
 391                  # Set the relaxation times (in s). 
 392                  self.interpreter.relax_disp.relax_time(spectrum_id=sp_id, time=time_sl) 
 393   
 394                  # Set the spectrometer frequency. 
 395                  self.interpreter.spectrometer.frequency(id=sp_id, frq=set_sfrq, units='MHz') 
 396   
 397                  # Add to counter 
 398                  j += 1 
 399   
 400   
 401          print("Testing the number of settings") 
 402          print("Number of settings iterations is: %s. Number of cdp.exp_type is: %s"%(i, len(cdp.exp_type))) 
 403          self.assertEqual(70, len(expfileslines)) 
 404          self.assertEqual(69, j) 
 405          self.assertEqual(69, len(cdp.exp_type)) 
 406   
 407          # Cluster spins 
 408          for curspin in cluster_ids: 
 409              print("Adding spin %s to cluster"%curspin) 
 410              self.interpreter.relax_disp.cluster('model_cluster', curspin) 
 411   
 412          # De-select for analysis those spins who have not been clustered 
 413          for free_spin in cdp.clustering['free spins']: 
 414              print("Deselecting free spin %s"%free_spin) 
 415              self.interpreter.deselect.spin(spin_id=free_spin, change_all=False) 
 416   
 417   
 418          #Paper         reference values 
 419          #              Resi   Resn         R1_rad_s   R1err_rad_s   R2_rad_s   R2err_rad_s   kEX_rad_s      kEXerr_rad_s  phi_rad2_s2     phierr_rad2_s2    phi_ppm2         phierr_ppm2 
 420          # Scaling rad2_s2 to ppm2: scaling_rad2_s2 = frequency_to_ppm(frq=1/(2*pi), B0=cdp.spectrometer_frq_list[0], isotope='15N')**2 = 3.85167990165e-06 
 421          ds.ref = dict() 
 422          ds.ref[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 423          ds.ref[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 424          ds.ref[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 425          ds.ref[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 426          ds.ref[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 427          ds.ref[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 428          ds.ref[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 429          ds.ref[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 430          ds.ref[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 431          ds.ref[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 432          ds.ref[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 433          ds.ref[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 434          ds.ref[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 435          ds.ref[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 436          ds.ref[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 437   
 438          ds.guess = dict() 
 439          ds.guess[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 440          ds.guess[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 441          ds.guess[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 442          ds.guess[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 443          ds.guess[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 444          ds.guess[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 445          ds.guess[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 446          ds.guess[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 447          ds.guess[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 448          ds.guess[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 449          ds.guess[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 450          ds.guess[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 451          ds.guess[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 452          ds.guess[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 453          ds.guess[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 454   
 455          # Assign guess values. 
 456          for spin, spin_id in spin_loop(return_id=True): 
 457              if spin_id in cluster_ids: 
 458                  print("spin_id %s in cluster ids"%(spin_id)) 
 459                  spin.kex = ds.guess[spin_id][6] 
 460                  spin.phi_ex = ds.guess[spin_id][10] 
 461              else: 
 462                  print("spin_id %s NOT in cluster ids"%(spin_id)) 
 463   
 464          if read_R1: 
 465              # Read the R1 data 
 466              self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
 467   
 468   
 469 -    def setup_hansen_cpmg_data(self, model=None): 
 470          """Set up the data for the test_hansen_cpmg_data_*() system tests. 
 471   
 472          @keyword model: The name of the model which will be tested. 
 473          @type model:    str 
 474          """ 
 475   
 476          # Create the data pipe and load the base data. 
 477          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 478          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 479          self.interpreter.results.read(data_path+sep+'base_pipe') 
 480          self.interpreter.deselect.spin(':4') 
 481   
 482          # Set the nuclear isotope data. 
 483          self.interpreter.spin.isotope('15N') 
 484   
 485          # Create the R2eff data pipe and load the results. 
 486          self.interpreter.pipe.create(pipe_name='R2eff - relax_disp', pipe_type='relax_disp') 
 487          self.interpreter.pipe.switch(pipe_name='R2eff - relax_disp') 
 488          self.interpreter.results.read(data_path+sep+'r2eff_pipe') 
 489          self.interpreter.deselect.spin(':4') 
 490   
 491          # The model data pipe. 
 492          pipe_name = "%s - relax_disp" % model 
 493          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 494          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 495   
 496          # Set the model. 
 497          self.interpreter.relax_disp.select_model(model=model) 
 498   
 499          # Copy the data. 
 500          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to=pipe_name, param='r2eff') 
 501   
 502   
 503 -    def setup_kteilum_fmpoulsen_makke_cpmg_data(self, model=None, expfolder=None): 
 504          """Set up the data for the test_kteilum_fmpoulsen_makke_cpmg_data_*() system tests. 
 505   
 506          @keyword model: The name of the model which will be tested. 
 507          @type model:    str 
 508          """ 
 509   
 510          # Create the data pipe and load the base data. 
 511          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder 
 512          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 513          self.interpreter.results.read(data_path+sep+'ini_setup_trunc') 
 514   
 515          # Create the R2eff data pipe and load the results. 
 516          self.interpreter.pipe.create(pipe_name='R2eff', pipe_type='relax_disp') 
 517          self.interpreter.pipe.switch(pipe_name='R2eff') 
 518          self.interpreter.results.read(data_path+sep+'r2eff_pipe_trunc') 
 519   
 520          # The model data pipe. 
 521          pipe_name = "%s - relax_disp" % model 
 522          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 523          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 524   
 525          # Set the model. 
 526          self.interpreter.relax_disp.select_model(model=model) 
 527   
 528          # Copy the data. 
 529          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 530   
 531   
 532 -    def setup_korzhnev_2005_data(self, data_list=[]): 
 533          """Set up the data for the test_korzhnev_2005_data_*() system tests using the 'NS MMQ 2-site' model. 
 534   
 535          This loads the proton-heteronuclear SQ, ZQ, DQ, and MQ (MMQ) data from: 
 536   
 537              - Dmitry M. Korzhnev, Philipp Neudecker, Anthony Mittermaier, Vladislav Yu. Orekhov, and Lewis E. Kay (2005)  Multiple-site exchange in proteins studied with a suite of six NMR relaxation dispersion experiments: An application to the folding of a Fyn SH3 domain mutant.  127, 15602-15611 (U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}). 
 538   
 539          It consists of the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
 540   
 541   
 542          @keyword data_list: The list of data to load.  It can contain 'SQ', '1H SQ', 'ZQ', 'DQ', 'MQ', and '1H MQ'. 
 543          @type data_list:    list of str 
 544          """ 
 545   
 546          # Create the data pipe and load the base data. 
 547          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
 548          self.interpreter.pipe.create(pipe_name='Korzhnev et al., 2005', pipe_type='relax_disp') 
 549   
 550          # Create the spin system. 
 551          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
 552          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
 553          self.interpreter.spin.element('H', spin_id='@H') 
 554          self.interpreter.spin.element('N', spin_id='@N') 
 555          self.interpreter.spin.isotope('1H', spin_id='@H') 
 556          self.interpreter.spin.isotope('15N', spin_id='@N') 
 557   
 558          # Define the magnetic dipole-dipole relaxation interaction. 
 559          self.interpreter.interatom.define(spin_id1=':9@N', spin_id2=':9@H', direct_bond=True) 
 560   
 561          # The spectral data - experiment ID, R2eff file name, experiment type, spin ID string, spectrometer frequency in Hertz, relaxation time. 
 562          data = [ 
 563              ['1H SQ', '1H_SQ_CPMG_500_MHz',  'hs_500.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 500e6, 0.03], 
 564              ['1H SQ', '1H_SQ_CPMG_600_MHz',  'hs_600.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 600e6, 0.03], 
 565              ['1H SQ', '1H_SQ_CPMG_800_MHz',  'hs_800.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 800e6, 0.03], 
 566              ['SQ',    '15N_SQ_CPMG_500_MHz', 'ns_500.res', EXP_TYPE_CPMG_SQ,        ':9@N', 500e6, 0.04], 
 567              ['SQ',    '15N_SQ_CPMG_600_MHz', 'ns_600.res', EXP_TYPE_CPMG_SQ,        ':9@N', 600e6, 0.04], 
 568              ['SQ',    '15N_SQ_CPMG_800_MHz', 'ns_800.res', EXP_TYPE_CPMG_SQ,        ':9@N', 800e6, 0.04], 
 569              ['DQ',    '15N_DQ_CPMG_500_MHz', 'dq_500.res', EXP_TYPE_CPMG_DQ,        ':9@N', 500e6, 0.03], 
 570              ['DQ',    '15N_DQ_CPMG_600_MHz', 'dq_600.res', EXP_TYPE_CPMG_DQ,        ':9@N', 600e6, 0.03], 
 571              ['DQ',    '15N_DQ_CPMG_800_MHz', 'dq_800.res', EXP_TYPE_CPMG_DQ,        ':9@N', 800e6, 0.03], 
 572              ['ZQ',    '15N_ZQ_CPMG_500_MHz', 'zq_500.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 500e6, 0.03], 
 573              ['ZQ',    '15N_ZQ_CPMG_600_MHz', 'zq_600.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 600e6, 0.03], 
 574              ['ZQ',    '15N_ZQ_CPMG_800_MHz', 'zq_800.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 800e6, 0.03], 
 575              ['1H MQ', '1H_MQ_CPMG_500_MHz',  'hm_500.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 500e6, 0.02], 
 576              ['1H MQ', '1H_MQ_CPMG_600_MHz',  'hm_600.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 600e6, 0.02], 
 577              ['1H MQ', '1H_MQ_CPMG_800_MHz',  'hm_800.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 800e6, 0.02], 
 578              ['MQ',    '15N_MQ_CPMG_500_MHz', 'nm_500.res', EXP_TYPE_CPMG_MQ,        ':9@N', 500e6, 0.02], 
 579              ['MQ',    '15N_MQ_CPMG_600_MHz', 'nm_600.res', EXP_TYPE_CPMG_MQ,        ':9@N', 600e6, 0.02], 
 580              ['MQ',    '15N_MQ_CPMG_800_MHz', 'nm_800.res', EXP_TYPE_CPMG_MQ,        ':9@N', 800e6, 0.02] 
 581          ] 
 582          cpmg_frqs_1h_sq = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
 583          cpmg_frqs_sq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 584          cpmg_frqs_dq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 585          cpmg_frqs_zq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 586          cpmg_frqs_1h_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 1000.0, 1500.0, 2000.0, 2500.0] 
 587          cpmg_frqs_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 588   
 589          # Loop over the files, reading in the data. 
 590          for data_type, id, file, exp_type, spin_id, H_frq, relax_time in data: 
 591              # Skip undesired data. 
 592              if data_type not in data_list: 
 593                  continue 
 594   
 595              # Alias the CPMG frequencies. 
 596              if data_type == 'SQ': 
 597                  cpmg_frqs = cpmg_frqs_sq 
 598              elif data_type == '1H SQ': 
 599                  cpmg_frqs = cpmg_frqs_1h_sq 
 600              elif data_type == 'DQ': 
 601                  cpmg_frqs = cpmg_frqs_dq 
 602              elif data_type == 'ZQ': 
 603                  cpmg_frqs = cpmg_frqs_zq 
 604              elif data_type == '1H MQ': 
 605                  cpmg_frqs = cpmg_frqs_1h_mq 
 606              elif data_type == 'MQ': 
 607                  cpmg_frqs = cpmg_frqs_mq 
 608   
 609              # Loop over each CPMG frequency. 
 610              for cpmg_frq in cpmg_frqs: 
 611                  # The id. 
 612                  new_id = "%s_%s" % (id, cpmg_frq) 
 613   
 614                  # Set the NMR field strength. 
 615                  self.interpreter.spectrometer.frequency(id=new_id, frq=H_frq) 
 616   
 617                  # Set the relaxation dispersion experiment type. 
 618                  self.interpreter.relax_disp.exp_type(spectrum_id=new_id, exp_type=exp_type) 
 619   
 620                  # Relaxation dispersion CPMG constant time delay T (in s). 
 621                  self.interpreter.relax_disp.relax_time(spectrum_id=new_id, time=relax_time) 
 622   
 623                  # Set the CPMG frequency. 
 624                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=new_id, cpmg_frq=cpmg_frq) 
 625   
 626              # Read the R2eff data. 
 627              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
 628   
 629          # Change the model. 
 630          self.interpreter.relax_disp.select_model('NS MMQ 2-site') 
 631   
 632   
 633 -    def setup_sod1wt_t25(self, pipe_name, pipe_type, pipe_name_r2eff, select_spin_index): 
 634          """Setup of data SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
 635   
 636          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
 637          'SOD1-WT' CPMG data to the CR72 dispersion model. 
 638   
 639          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
 640          Data is for experiment at 25 degree Celcius. 
 641          """ 
 642   
 643          # Create the data pipe and load the base data. 
 644          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'sod1wt_t25' 
 645   
 646          # Set experiment settings. sfrq, time_T2, ncyc 
 647          Exps = [ 
 648          ["600MHz", "Z_A", 599.8908617*1E6, 0.06, [28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 50, 18, 40, 6, 12, 0, 24], ["Z_A1", "Z_A15"] ], 
 649          ["500MHz", "Z_B", 499.862139*1E6, 0.04, [20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0], ["Z_B1", "Z_B18"] ] ] 
 650   
 651          # Create base pipe 
 652          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 653   
 654          # Loop throug experiments 
 655          id_lists = [] 
 656          for folder, key, sfrq, time_T2, ncycs, rep_ncyss in Exps: 
 657              # Read spins 
 658              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 659              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 660   
 661              # Make spectrum id list 
 662              id_list = list(key+str(i) for i in range(len(ncycs))) 
 663              id_lists.append(id_list) 
 664   
 665              # Read intensities 
 666              self.interpreter.spectrum.read_intensities(file="128_FT.ser", dir=data_path+sep+folder, int_method='height', spectrum_id=id_list, int_col=list(range(len(id_list))) ) 
 667   
 668              # Loop over experiments 
 669              for i in range(len(ncycs)): 
 670                  ncyc = ncycs[i] 
 671                  vcpmg = ncyc/time_T2 
 672   
 673                  # Test if spectrum is a reference 
 674                  if float(vcpmg) == 0.0: 
 675                      vcpmg = None 
 676                  else: 
 677                      vcpmg = round(float(vcpmg), 3) 
 678   
 679                  # Set current id 
 680                  current_id = id_list[i] 
 681   
 682                  # Set the current experiment type. 
 683                  self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
 684   
 685                  # Set the NMR field strength of the spectrum. 
 686                  self.interpreter.spectrometer.frequency(id=current_id, frq=sfrq, units='Hz') 
 687   
 688                  # Relaxation dispersion CPMG constant time delay T (in s). 
 689                  self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
 690   
 691                  # Set the relaxation dispersion CPMG frequencies. 
 692                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
 693   
 694          # Define replicated 
 695          self.interpreter.spectrum.replicated(spectrum_ids=Exps[0][5]) 
 696          self.interpreter.spectrum.replicated(spectrum_ids=Exps[1][5]) 
 697   
 698          # Perform error analysis 
 699          self.interpreter.spectrum.error_analysis(subset=id_lists[0]) 
 700          self.interpreter.spectrum.error_analysis(subset=id_lists[1]) 
 701   
 702          # Define isotope 
 703          self.interpreter.spin.isotope(isotope='15N') 
 704   
 705          ############# 
 706   
 707          # Define the 64 residues which was used for Global fitting 
 708          glob_assn = ["G10N-H", "D11N-H", "Q15N-H", "G16N-H", "G37N-H", "G41N-H", "L42N-H", "H43N-H", "H46N-H", "V47N-H", "E49N-H", 
 709          "E50N-H", "E51N-H", "N53N-H", "T54N-H", "G56N-H", "C57N-H", "T58N-H", "G61N-H", "H63aN-H", "F64aN-H", "N65aN-H", 
 710          "L67N-H", "S68N-H", "K70N-H", "G72N-H", "G73N-H", "K75N-H", "E78N-H", "R79N-H", "H80N-H", "V81N-H", "G82N-H", 
 711          "G85N-H", "N86N-H", "V87N-H", "S102N-H", "V103N-H", "I104N-H", "S105N-H", "A111N-H", "I112N-H", "R115N-H", 
 712          "V118N-H", "E121N-H", "A123N-H", "L126N-H", "G127N-H", "K128N-H", "G129N-H", "G130N-H", "N131N-H", "E133N-H", 
 713          "S134N-H", "T135N-H", "T137N-H", "G138N-H", "N139N-H", "A140N-H", "G141N-H", "S142N-H", "R143N-H", "C146N-H", "G147N-H"] 
 714   
 715          # Test number of global 
 716          self.assertEqual(64, len(glob_assn )) 
 717   
 718          ## Turn assignments into relax spin ids. 
 719          # Define regular expression search 
 720          r = re.compile("([a-zA-Z]+)([0-9]+)([a-zA-Z]+)") 
 721   
 722          # Create list to hold regular expression search 
 723          relax_glob_ids = [] 
 724   
 725          # Loop over assignments 
 726          for assn in glob_assn: 
 727              # Make match for the regular search 
 728              m = r.match(assn) 
 729              # Convert to relax spin string 
 730              relax_string = ":%s@%s"%(m.group(2), m.group(3)) 
 731   
 732              # Save the relax spin string and the regular search 
 733              relax_glob_ids.append([m.group(0), m.group(1), m.group(2), m.group(3), relax_string]) 
 734   
 735          ############# Deselect all spins, and select few spins 
 736   
 737          ## Deselect all spins, and select a few for analysis 
 738          self.interpreter.deselect.all() 
 739   
 740          # Select few spins 
 741          for i in select_spin_index: 
 742              self.interpreter.select.spin(spin_id=relax_glob_ids[i][4], change_all=False) 
 743   
 744          ############## 
 745   
 746          # Prepare for R2eff calculation 
 747          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 748          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 749   
 750          # Select model for points calculation 
 751          MODEL = "R2eff" 
 752          self.interpreter.relax_disp.select_model(model=MODEL) 
 753          # Calculate R2eff values 
 754          self.interpreter.minimise.calculate(verbosity=1) 
 755   
 756   
 757 -    def setup_missing_r1_spins(self): 
 758          """Function for setting up a few spins for the given pipe.""" 
 759   
 760          # Path to file. 
 761          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 762   
 763          # File with spins. 
 764          file = open(data_path+sep+'R1_fitted_values.txt') 
 765          lines = file.readlines() 
 766          file.close() 
 767   
 768          for i, line in enumerate(lines): 
 769              # Make the string test 
 770              line_split = line.split() 
 771   
 772              if line_split[0] == "#": 
 773                  continue 
 774   
 775              mol_name = line_split[0] 
 776              mol_name = None 
 777              res_num = int(line_split[1]) 
 778              res_name = line_split[2] 
 779              spin_num = line_split[3] 
 780              spin_num = None 
 781              spin_name = line_split[4] 
 782   
 783              # Create the spin. 
 784              self.interpreter.spin.create(spin_name=spin_name, spin_num=spin_num, res_name=res_name, res_num=res_num, mol_name=mol_name) 
 785   
 786   
 787 -    def setup_tp02_data_to_ns_r1rho_2site(self, clustering=False): 
 788          """Setup data for the test of relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
 789   
 790          # Reset. 
 791          self.interpreter.reset() 
 792   
 793          # Create the data pipe and load the base data. 
 794          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
 795          self.interpreter.state.load(data_path+sep+'r2eff_values') 
 796   
 797          # The model data pipe. 
 798          model = 'NS R1rho 2-site' 
 799          pipe_name = "%s - relax_disp" % model 
 800          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 801          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 802   
 803          # Set the model. 
 804          self.interpreter.relax_disp.select_model(model=model) 
 805   
 806          # Copy the data. 
 807          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 808   
 809          # Alias the spins. 
 810          spin1 = cdp.mol[0].res[0].spin[0] 
 811          spin2 = cdp.mol[0].res[1].spin[0] 
 812   
 813          # The R20 keys. 
 814          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
 815          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
 816   
 817          # Set the initial parameter values. 
 818          spin1.r2 = {r20_key1: 9.9963793866185, r20_key2: 15.0056724422684} 
 819          spin1.pA = 0.779782428085762 
 820          spin1.dw = 7.57855284496424 
 821          spin1.kex = 1116.7911285203 
 822          spin2.r2 = {r20_key1: 11.9983346935434, r20_key2: 18.0076097513337} 
 823          spin2.pA = 0.826666229688602 
 824          spin2.dw = 9.5732624231366 
 825          spin2.kex = 1380.46162655657 
 826   
 827          # Test the values when clustering. 
 828          if clustering: 
 829              self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-100") 
 830   
 831          # Low precision optimisation. 
 832          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
 833   
 834          # Printout. 
 835          print("\n\nOptimised parameters:\n") 
 836          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
 837          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
 838          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
 839          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
 840          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
 841          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
 842          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
 843   
 844   
 845 -    def test_baldwin_synthetic(self): 
 846          """Test synthetic data of Andrew J. Baldwin B14 model  whereby the simplification R20A = R20B is assumed. 
 847   
 848          Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
 849   
 850          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>} with R20A, R20B = 2. rad/s. 
 851          """ 
 852   
 853          # The path to the data files. 
 854          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
 855   
 856          # Create pipe 
 857          pipe_name = 'base pipe' 
 858          pipe_type = 'relax_disp' 
 859          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
 860   
 861          # Create base pipe 
 862          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 863   
 864          # Generate the sequence. 
 865          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
 866   
 867          # Define the isotope. 
 868          self.interpreter.spin.isotope('1H', spin_id='@H') 
 869   
 870          # Build the experiment IDs. 
 871          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
 872          ncycs = [2, 4, 8, 10, 20, 40, 500] 
 873          ids = [] 
 874          for ncyc in ncycs: 
 875              ids.append('CPMG_%s' % ncyc) 
 876   
 877          print("\n\nThe experiment IDs are %s." % ids) 
 878   
 879          # Set up the metadata for the experiments. 
 880          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
 881          sfrq = 200. * 1E6 
 882   
 883          # Total time of CPMG block. 
 884          Trelax = 0.04 
 885   
 886          # First set the 
 887          for i in range(len(ids)): 
 888              id = ids[i] 
 889              # Set the spectrometer frequency. 
 890              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
 891   
 892              # Set the experiment type. 
 893              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
 894   
 895              # Set the relaxation dispersion CPMG constant time delay T (in s). 
 896              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
 897   
 898              # Set the relaxation dispersion CPMG frequencies. 
 899              ncyc = ncycs[i] 
 900              nu_cpmg = ncyc / Trelax 
 901              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
 902   
 903          # Prepare for R2eff reading. 
 904          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 905          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 906   
 907          # Try reading the R2eff file. 
 908          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_r2a_eq_r2b_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
 909   
 910          # Check the global data. 
 911          data = [ 
 912              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
 913              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
 914              ['dispersion_points', len(ncycs)], 
 915              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
 916              ['exp_type_list', ['SQ CPMG']], 
 917              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
 918              ['spectrometer_frq_count', 1], 
 919              ['spectrometer_frq_list', [sfrq]], 
 920              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
 921          ] 
 922          for name, value in data: 
 923              # Does it exist? 
 924              self.assert_(hasattr(cdp, name)) 
 925   
 926              # Check the object. 
 927              obj = getattr(cdp, name) 
 928              if not isinstance(data, dict): 
 929                  self.assertEqual(obj, value) 
 930   
 931              # Check the global dictionary data. 
 932              else: 
 933                  for id in ids: 
 934                      self.assertEqual(obj[id], value[id]) 
 935   
 936          # Check the spin data. 
 937          n_data = [ 
 938              [ 50.000000, 10.367900, 0.1], 
 939              [ 100.000000, 10.146849, 0.1], 
 940              [ 200.000000, 9.765987, 0.1], 
 941              [ 250.000000, 9.409789, 0.1], 
 942              [ 500.000000, 5.829819, 0.1], 
 943              [ 1000.000000, 3.191928, 0.1], 
 944              [ 12500.000000, 2.008231, 0.1] 
 945          ] 
 946          for disp_point, value, error in n_data: 
 947              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
 948              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
 949              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
 950   
 951          # Generate r20 key. 
 952          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
 953   
 954          ## Now prepare for MODEL calculation. 
 955          MODEL = "B14" 
 956   
 957          # Change pipe. 
 958          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
 959          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
 960          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 961   
 962          # Then select model. 
 963          self.interpreter.relax_disp.select_model(model=MODEL) 
 964   
 965          # Store grid and minimisations results. 
 966          grid_results = [] 
 967          mini_results = [] 
 968   
 969          # The grid search size (the number of increments per dimension). 
 970          # If None, use the default values. 
 971          #GRID = None 
 972          GRID = 13 
 973          # Perform Grid Search. 
 974          if GRID: 
 975              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
 976              # This speeds it up considerably. 
 977              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
 978   
 979              # Then do grid search. 
 980              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
 981   
 982              # If no Grid search, set the default values. 
 983          else: 
 984              for param in MODEL_PARAMS[MODEL]: 
 985                  self.interpreter.value.set(param=param, index=None) 
 986                  # Do a grid search, which will store the chi2 value. 
 987              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
 988   
 989          # Store result. 
 990          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
 991              grid_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
 992   
 993          ## Now do minimisation. 
 994          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
 995          set_func_tol = 1e-10 
 996          set_max_iter = 1000 
 997          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
 998   
 999          # Store result. 
1000          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1001              mini_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1002   
1003          # Print results. 
1004          for i in range(len(grid_results)): 
1005              g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1006              m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1007              print("GRID %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1008              print("MIN  %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1009   
1010          # Reference values from Baldwin.py. 
1011          # Exchange rate = k+ + k- (s-1) 
1012          kex = 1000. 
1013          # Fractional population of excited state k+/kex 
1014          pb = 0.01 
1015          # deltaOmega in ppm 
1016          dw_ppm = 2. 
1017          #relaxation rate of ground (s-1) 
1018          R2g = 2. 
1019          #relaxation rate of excited (s-1) 
1020          R2e = 2. 
1021   
1022          # Test the parameters which created the data. 
1023          # This is for the 1H spin. 
1024          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key], R2g, 6) 
1025   
1026          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1027          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 8) 
1028          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 3) 
1029   
1030   
1031 -    def test_baldwin_synthetic_full(self): 
1032          """Test synthetic data of Andrew J. Baldwin B14 model. Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
1033   
1034          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>}. 
1035          """ 
1036   
1037          # The path to the data files. 
1038          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
1039   
1040          # Create pipe 
1041          pipe_name = 'base pipe' 
1042          pipe_type = 'relax_disp' 
1043          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
1044   
1045          # Create base pipe 
1046          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
1047   
1048          # Generate the sequence. 
1049          # Generate both a 1H spin, and 15N spin. 
1050          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
1051   
1052          # Define the isotope. 
1053          self.interpreter.spin.isotope('1H', spin_id='@H') 
1054   
1055          # Build the experiment IDs. 
1056          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
1057          ncycs = [2, 4, 8, 10, 20, 40, 500] 
1058          ids = [] 
1059          for ncyc in ncycs: 
1060              ids.append('CPMG_%s' % ncyc) 
1061   
1062          print("\n\nThe experiment IDs are %s." % ids) 
1063   
1064          # Set up the metadata for the experiments. 
1065          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
1066          sfrq = 200. * 1E6 
1067   
1068          # Total time of CPMG block. 
1069          Trelax = 0.04 
1070   
1071          # First set the 
1072          for i in range(len(ids)): 
1073              id = ids[i] 
1074              # Set the spectrometer frequency. 
1075              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
1076   
1077              # Set the experiment type. 
1078              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
1079   
1080              # Set the relaxation dispersion CPMG constant time delay T (in s). 
1081              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
1082   
1083              # Set the relaxation dispersion CPMG frequencies. 
1084              ncyc = ncycs[i] 
1085              nu_cpmg = ncyc / Trelax 
1086              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
1087   
1088          # Prepare for R2eff reading. 
1089          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
1090          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
1091   
1092          # Try reading the R2eff file. 
1093          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
1094   
1095          # Check the global data. 
1096          data = [ 
1097              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
1098              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
1099              ['dispersion_points', len(ncycs)], 
1100              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
1101              ['exp_type_list', ['SQ CPMG']], 
1102              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
1103              ['spectrometer_frq_count', 1], 
1104              ['spectrometer_frq_list', [sfrq]], 
1105              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
1106          ] 
1107          for name, value in data: 
1108              # Does it exist? 
1109              self.assert_(hasattr(cdp, name)) 
1110   
1111              # Check the object. 
1112              obj = getattr(cdp, name) 
1113              if not isinstance(data, dict): 
1114                  self.assertEqual(obj, value) 
1115   
1116              # Check the global dictionary data. 
1117              else: 
1118                  for id in ids: 
1119                      self.assertEqual(obj[id], value[id]) 
1120   
1121          # Check the spin data. 
1122          n_data = [ 
1123              [ 50.000000, 10.286255, 0.1], 
1124              [ 100.000000, 10.073083, 0.1], 
1125              [ 200.000000, 9.692746, 0.1], 
1126              [ 250.000000, 9.382441, 0.1], 
1127              [ 500.000000, 6.312396, 0.1], 
1128              [ 1000.000000, 3.957029, 0.1], 
1129              [ 12500.000000, 2.880420, 0.1] 
1130          ] 
1131          for disp_point, value, error in n_data: 
1132              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
1133              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
1134              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
1135   
1136          # Generate r20 key. 
1137          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
1138   
1139          ## Now prepare for MODEL calculation. 
1140          MODEL = "B14 full" 
1141   
1142          # Change pipe. 
1143          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
1144          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
1145          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
1146   
1147          # Then select model. 
1148          self.interpreter.relax_disp.select_model(model=MODEL) 
1149   
1150          # Store grid and minimisations results. 
1151          grid_results = [] 
1152          mini_results = [] 
1153          clust_results = [] 
1154   
1155          # The grid search size (the number of increments per dimension). 
1156          # If None, use the default values. 
1157          #GRID = None 
1158          GRID = 13 
1159          # Perform Grid Search. 
1160          if GRID: 
1161              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
1162              # This speeds it up considerably. 
1163              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
1164   
1165              # Then do grid search. 
1166              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
1167   
1168              # If no Grid search, set the default values. 
1169          else: 
1170              for param in MODEL_PARAMS[MODEL]: 
1171                  self.interpreter.value.set(param=param, index=None) 
1172                  # Do a grid search, which will store the chi2 value. 
1173              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
1174   
1175          # Store result. 
1176          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1177              grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1178   
1179          ## Now do minimisation. 
1180          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1181          set_func_tol = 1e-11 
1182          set_max_iter = 10000 
1183          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1184   
1185          # Store result. 
1186          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1187              mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1188   
1189          print("\n# Now print before and after minimisation-\n") 
1190   
1191          # Print results. 
1192          for i in range(len(grid_results)): 
1193              g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1194              m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1195              print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1196              print("MIN  %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1197   
1198          # Reference values from Baldwin.py. 
1199          # Exchange rate = k+ + k- (s-1) 
1200          kex = 1000. 
1201          # Fractional population of excited state k+/kex 
1202          pb = 0.01 
1203          # deltaOmega in ppm 
1204          dw_ppm = 2. 
1205          #relaxation rate of ground (s-1) 
1206          R2g = 2. 
1207          #relaxation rate of excited (s-1) 
1208          R2e = 100. 
1209   
1210          # Test the parameters which created the data. 
1211          # This is for the 1H spin. 
1212          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key], R2g, 3) 
1213          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key]/100, R2e/100, 3) 
1214   
1215          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1216          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6) 
1217          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex/1000, kex/1000, 2) 
1218   
1219   
1220 -    def x_test_bmrb_sub_cpmg(self): 
1221          """U{Task #7858: <https://gna.org/task/?7858>} Make it possible to submit CPMG experiments for BMRB. 
1222          This uses CPMG data from: 
1223              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE. 
1224                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
1225                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, DOI 10.1002/prot.22886 
1226          """ 
1227   
1228          # Define path to data  
1229          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
1230   
1231          # Read data. 
1232          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
1233   
1234          # Set element 
1235          self.interpreter.spin.element(element='N', spin_id=':*@N', force=False) 
1236          #self.interpreter.spin.isotope(isotope='15N', spin_id=':*@N', force=False) 
1237          # Rename molecule from None to 'HEWL' 
1238          self.interpreter.molecule.name(mol_id=None, name='HEWL', force=True) 
1239          self.interpreter.molecule.type(mol_id='#HEWL', type='protein', force=False) 
1240   
1241          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1242              print(spin_id) 
1243              if resn == 'C': 
1244                  print(resi, resn) 
1245   
1246          # Select the thiol state of the system. 
1247          # 'all disulfide bound', 'all free', 'all other bound', 'disulfide and other bound', 'free and disulfide bound', 'free and other bound', 'free disulfide and other bound', 'not available', 'not present', 'not reported', 'unknown' 
1248          self.interpreter.bmrb.thiol_state(state='not reported') 
1249   
1250          # relax_data.temp_calibration(ri_id=None, method=None) 
1251   
1252          # Call display of bmrb. 
1253          self.interpreter.bmrb.display() 
1254   
1255   
1256 -    def test_bug_21081_disp_cluster_fail(self): 
1257          """U{Bug #21081<https://gna.org/bugs/?21081>} catch, the failure of a cluster analysis when spins are deselected.""" 
1258   
1259          # Clear the data store. 
1260          self.interpreter.reset() 
1261   
1262          # Load the state. 
1263          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21081_disp_cluster_fail.bz2' 
1264          self.interpreter.state.load(state, force=True) 
1265   
1266          # Model selection - to catch the failure. 
1267          self.interpreter.model_selection(method='AIC', modsel_pipe='final', bundle='relax_disp', pipes=['No Rex', 'CR72']) 
1268   
1269   
1270 -    def test_bug_21460_disp_cluster_fail(self): 
1271          """U{Bug #21460<https://gna.org/bugs/?21460>} catch, the failure due to a spectrometer frequency having no relaxation data.""" 
1272   
1273          # Clear the data store. 
1274          self.interpreter.reset() 
1275   
1276          # Load the state. 
1277          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21460_bad_fields.bz2' 
1278          self.interpreter.state.load(state, force=True) 
1279   
1280          # Execute the auto-analysis (fast). 
1281          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1282          relax_disp.Relax_disp.opt_max_iterations = 1000 
1283          relax_disp.Relax_disp(pipe_name="origin - relax_disp (Thu Jan  2 13:46:44 2014)", pipe_bundle="relax_disp (Thu Jan  2 13:46:44 2014)", results_dir=self.tmpdir, models=['R2eff', 'No Rex', 'CR72', 'NS CPMG 2-site expanded'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1284   
1285   
1286 -    def test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp(self): 
1287          """U{Bug #21665<https://gna.org/bugs/?21344>} catch, the failure of an analysis of a sparse acquired R1rho dataset with missing combinations of time and spin-lock field strengths using auto_analysis.""" 
1288   
1289          # Clear the data store. 
1290          self.interpreter.reset() 
1291   
1292          # Load the state. 
1293          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
1294          self.interpreter.state.load(state, force=True) 
1295   
1296          # Execute the auto-analysis (fast). 
1297          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1298          relax_disp.Relax_disp.opt_max_iterations = 1000 
1299          relax_disp.Relax_disp(pipe_name='base pipe', pipe_bundle='relax_disp', results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1300   
1301   
1302 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_calc(self): 
1303          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using minimise.calculate().""" 
1304   
1305          # Clear the data store. 
1306          self.interpreter.reset() 
1307   
1308          # Load the state. 
1309          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1310          self.interpreter.state.load(state, force=True) 
1311   
1312          # Run the calculation. 
1313          self.interpreter.minimise.calculate(verbosity=1) 
1314   
1315   
1316 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_relax_disp(self): 
1317          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times using auto_analysis.""" 
1318   
1319          # Clear the data store. 
1320          self.interpreter.reset() 
1321   
1322          # Load the state. 
1323          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1324          self.interpreter.state.load(state, force=True) 
1325   
1326          # Execute the auto-analysis (fast). 
1327          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1328          relax_disp.Relax_disp.opt_max_iterations = 1000 
1329          relax_disp.Relax_disp(pipe_name="compare_128_FT_R2eff", pipe_bundle="cpmg_disp_sod1d90a", results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1330   
1331   
1332 -    def test_bug_21715_clustered_indexerror(self): 
1333          """Catch U{bug #21715<https://gna.org/bugs/?21715>}, the failure of a clustered auto-analysis due to an IndexError.""" 
1334   
1335          # Clear the data store. 
1336          self.interpreter.reset() 
1337   
1338          # Load the state. 
1339          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'state.bz2' 
1340          self.interpreter.state.load(state, force=True) 
1341   
1342          # Execute the auto-analysis (fast). 
1343          pre_run_dir = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'non_clustered' 
1344          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1345          relax_disp.Relax_disp.opt_max_iterations = 1000 
1346          relax_disp.Relax_disp(pipe_name='origin - relax_disp (Sun Feb 23 19:36:51 2014)', pipe_bundle='relax_disp (Sun Feb 23 19:36:51 2014)', results_dir=self.tmpdir, models=['R2eff', 'No Rex'], grid_inc=11, mc_sim_num=3, modsel='AIC', pre_run_dir=pre_run_dir, insignificance=1.0, numeric_only=True, mc_sim_all_models=False, eliminate=True) 
1347   
1348   
1349 -    def test_bug_22146_unpacking_r2a_r2b_cluster_B14(self): 
1350          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered B14 full analysis.""" 
1351   
1352          # Base data setup. 
1353          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='B14_full', model_analyse = MODEL_B14_FULL) 
1354   
1355   
1356 -    def test_bug_22146_unpacking_r2a_r2b_cluster_CR72(self): 
1357          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered CR72 full analysis.""" 
1358   
1359          # Base data setup. 
1360          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='CR72_full', model_analyse = MODEL_CR72_FULL) 
1361   
1362   
1363 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_3D(self): 
1364          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE 3D full analysis.""" 
1365   
1366          # Base data setup. 
1367          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_3d_full', model_analyse = MODEL_NS_CPMG_2SITE_3D_FULL) 
1368   
1369   
1370 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_STAR(self): 
1371          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE STAR full analysis.""" 
1372   
1373          # Base data setup. 
1374          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_star_full', model_analyse = MODEL_NS_CPMG_2SITE_STAR_FULL, places = 4) 
1375   
1376   
1377 -    def test_bug_22477_grace_write_k_AB_mixed_analysis(self): 
1378          """Catch U{bug #22146<https://gna.org/bugs/?22477>}, the failure of issuing: grace.write(x_data_type='res_num', y_data_type=param) for a mixed CPMG analysis.""" 
1379   
1380          # Clear the data store. 
1381          self.interpreter.reset() 
1382   
1383          # Load the state. 
1384          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22477_grace_write_k_AB_mixed_analysis'+sep+'bug_22477_results.bz2' 
1385          self.interpreter.state.load(state, force=True) 
1386   
1387          param = 'k_AB' 
1388   
1389          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1390              print(spin_id, spin.params) 
1391              if param in spin.params: 
1392                  print(spin_id, spin.k_AB, spin.k_AB_err) 
1393   
1394          # Perform write. 
1395          self.interpreter.grace.write(x_data_type='res_num', y_data_type=param, file='%s.agr'%param, dir=self.tmpdir, force=True) 
1396   
1397   
1398          # Test the header of the value.write  parameter r2. 
1399          param = 'r2' 
1400          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1401   
1402          file = open(self.tmpdir+sep+'%s.out'%param) 
1403          lines = file.readlines() 
1404          file.close() 
1405   
1406          for i, line in enumerate(lines): 
1407              # Make the string test 
1408              line_split = line.split() 
1409              print(line_split) 
1410   
1411              if len(line_split) > 1: 
1412                  # Break at parameter header. 
1413                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1414                      nr_split_header = len(line_split) 
1415                      nr_split_header_i = i 
1416                      break 
1417   
1418          # Call the line after. 
1419          line_split_val = lines[nr_split_header_i + 1].split() 
1420          print(line_split_val) 
1421   
1422          # Assert that the number of columns is equal, plus 1 for "#". 
1423          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1424   
1425          # Test the header of the value.write for parameter r2eff. 
1426          param = 'r2eff' 
1427          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1428   
1429          file = open(self.tmpdir+sep+'%s.out'%param) 
1430          lines = file.readlines() 
1431          file.close() 
1432   
1433          for i, line in enumerate(lines): 
1434              # Make the string test 
1435              line_split = line.split() 
1436              print(line_split) 
1437   
1438              if len(line_split) > 1: 
1439                  # Break at parameter header. 
1440                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1441                      nr_split_header = len(line_split) 
1442                      nr_split_header_i = i 
1443                      break 
1444   
1445          # Call the line after. 
1446          line_split_val = lines[nr_split_header_i + 1].split() 
1447          print(line_split_val) 
1448   
1449          # Assert that the number of columns is equal, plus 1 for "#". 
1450          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1451   
1452   
1453 -    def test_bug_23186_cluster_error_calc_dw(self): 
1454          """Catch U{bug #23186<https://gna.org/bugs/?23186>}: Error calculation of individual parameter "dw" from Monte-Carlo, is based on first spin.""" 
1455   
1456          # Clear the data store. 
1457          self.interpreter.reset() 
1458   
1459          # Load the state. 
1460          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_23186.bz2' 
1461          self.interpreter.state.load(state, force=True) 
1462   
1463          # Dic key to spectrometer frq. 
1464          dickey = 'SQ CPMG - 599.89086220 MHz' 
1465   
1466          # First get the resi 0 array of sim r2a. 
1467          resi_0_r2a = [] 
1468   
1469          # Assign spins 
1470          res0 = cdp.mol[0].res[0].spin[0] 
1471          res1 = cdp.mol[0].res[1].spin[0] 
1472   
1473          print("Chi2 before call to minimise: %3.3f"%res0.chi2) 
1474          self.interpreter.minimise.execute(min_algor='simplex', max_iter=100000, verbosity=0) 
1475          print("Chi2 after call to minimise: %3.3f"%res0.chi2) 
1476   
1477          # Loop over the dics in spin. 
1478          for cdic in res0.r2a_sim: 
1479              resi_0_r2a.append(cdic[dickey]) 
1480   
1481          # Get stats with numpy 
1482          resi_0_r2a_std = std(asarray(resi_0_r2a), ddof=1) 
1483   
1484          # First get the resi 86 array of sim r2a. 
1485          resi_86_r2a = [] 
1486   
1487          # Loop over the dics in spin. 
1488          for cdic in res1.r2a_sim: 
1489              resi_86_r2a.append(cdic[dickey]) 
1490   
1491          # Get stats with numpy 
1492          resi_86_r2a_std = std(asarray(resi_86_r2a), ddof=1) 
1493   
1494          # Then get for dw. 
1495   
1496          # First get the array of sim dw. 
1497          resi_0_dw = res0.dw_sim 
1498          resi_86_dw = res1.dw_sim 
1499   
1500          # Get stats with numpy 
1501          resi_0_dw_std = std(asarray(resi_0_dw), ddof=1) 
1502          resi_86_dw_std = std(asarray(resi_86_dw), ddof=1) 
1503   
1504          # Then get for spin independent parameter. 
1505   
1506          # First get the array of sim dw. 
1507          resi_0_kAB = res0.k_AB_sim 
1508          resi_86_kAB = res1.k_AB_sim 
1509   
1510          # Get stats with numpy 
1511          resi_0_kAB_std = std(asarray(resi_0_kAB), ddof=1) 
1512          resi_86_kAB_std = std(asarray(resi_0_kAB), ddof=1) 
1513   
1514          # Assume they both std of k_AB values are equal 
1515          self.assertEqual(resi_0_kAB_std, resi_86_kAB_std) 
1516   
1517          # Perform error analysis. 
1518          self.interpreter.monte_carlo.error_analysis() 
1519   
1520          # Check values for k_AB. 
1521          self.assertAlmostEqual(resi_0_kAB_std, res0.k_AB_err) 
1522          self.assertAlmostEqual(resi_86_kAB_std, res1.k_AB_err) 
1523   
1524          # Check values for r2a. 
1525          self.assertAlmostEqual(resi_0_r2a_std, res0.r2a_err[dickey]) 
1526          self.assertAlmostEqual(resi_86_r2a_std, res1.r2a_err[dickey]) 
1527   
1528          # Check values for dw. 
1529          self.assertAlmostEqual(resi_0_dw_std, res0.dw_err) 
1530          self.assertAlmostEqual(resi_86_dw_std, res1.dw_err) 
1531   
1532          # The following is for Bug #23619: (https://gna.org/bugs/index.php?23619): Stored chi2 sim values from Monte-Carlo simulations does not equal normal chi2 values. 
1533          # This is to show that this bug is invalid. The "very" different chi2 values stems from r2eff points being back-calculated values rather than original measured values. 
1534   
1535          # Check calculates the same Monte-Carlo chi2 values  
1536          self.interpreter.monte_carlo.setup(number=3) 
1537          self.interpreter.monte_carlo.create_data(method='back_calc') 
1538          self.interpreter.monte_carlo.initial_values() 
1539   
1540          # Assign original data instead of back_calculated error. 
1541          res0.r2eff_sim[0] = copy.copy(res0.r2eff) 
1542          res0.r2eff_sim[1] = copy.copy(res0.r2eff) 
1543          res0.r2eff_sim[2] = copy.copy(res0.r2eff) 
1544          res1.r2eff_sim[0] = copy.copy(res1.r2eff) 
1545          res1.r2eff_sim[1] = copy.copy(res1.r2eff) 
1546          res1.r2eff_sim[2] = copy.copy(res1.r2eff) 
1547   
1548          self.interpreter.minimise.execute(min_algor='simplex', max_iter=100000) 
1549          self.interpreter.monte_carlo.error_analysis() 
1550   
1551          # Get the simulation array and calculate the average 
1552          spin_chi2_mc = res0.chi2 
1553          spin_chi2_mc_sim = res0.chi2_sim 
1554          spin_chi2_mc_sim_ave = average(spin_chi2_mc_sim) 
1555   
1556          print("The chi2 from calculation is: %3.3f"%spin_chi2_mc) 
1557          print("The array with monte-carlo chi2 values is: %s"%spin_chi2_mc_sim) 
1558          print("The average of this array is: %3.3f"%spin_chi2_mc_sim_ave) 
1559   
1560          self.assertAlmostEqual(spin_chi2_mc, spin_chi2_mc_sim_ave, 7) 
1561   
1562   
1563 -    def test_bug_9999_slow_r1rho_r2eff_error_with_mc(self): 
1564          """Catch U{bug #9999<https://gna.org/bugs/?9999>}, The slow optimisation of R1rho R2eff error estimation with Monte Carlo simulations.""" 
1565   
1566          # Define path to data  
1567          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
1568   
1569          # Read data. 
1570          self.interpreter.results.read(prev_data_path + sep + 'results')         
1571   
1572          # Now count number 
1573          graph_nr = 1 
1574          for exp_type, frq, offset, point in loop_exp_frq_offset_point(return_indices=False): 
1575              print("\nGraph nr %i" % graph_nr) 
1576              for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
1577                  print(exp_type, frq, offset, point, time) 
1578              graph_nr += 1 
1579   
1580          ## Possibly do an error analysis. 
1581   
1582          # Check if intensity errors have already been calculated by the user. 
1583          precalc = True 
1584          for spin in spin_loop(skip_desel=True): 
1585              # No structure. 
1586              if not hasattr(spin, 'peak_intensity_err'): 
1587                  precalc = False 
1588                  break 
1589   
1590              # Determine if a spectrum ID is missing from the list. 
1591              for id in cdp.spectrum_ids: 
1592                  if id not in spin.peak_intensity_err: 
1593                      precalc = False 
1594                      break 
1595   
1596          # Skip. 
1597          if precalc: 
1598              print("Skipping the error analysis as it has already been performed.") 
1599   
1600          else: 
1601              # Loop over the spectrometer frequencies. 
1602              for frq in loop_frq(): 
1603                  # Generate a list of spectrum IDs matching the frequency. 
1604                  ids = [] 
1605                  for id in cdp.spectrum_ids: 
1606                      # Check that the spectrometer frequency matches. 
1607                      match_frq = True 
1608                      if frq != None and cdp.spectrometer_frq[id] != frq: 
1609                          match_frq = False 
1610   
1611                      # Add the ID. 
1612                      if match_frq: 
1613                          ids.append(id) 
1614   
1615                  # Run the error analysis on the subset. 
1616                  self.interpreter.spectrum.error_analysis(subset=ids) 
1617   
1618          print("has_exponential_exp_type:", has_exponential_exp_type()) 
1619   
1620          model = 'R2eff' 
1621          self.interpreter.relax_disp.select_model(model) 
1622   
1623          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1624              #delattr(spin, 'r2eff') 
1625              #delattr(spin, 'r2eff_err') 
1626              #delattr(spin, 'i0') 
1627              #delattr(spin, 'i0_err') 
1628              setattr(spin, 'r2eff', {}) 
1629              setattr(spin, 'r2eff_err', {}) 
1630              setattr(spin, 'i0', {}) 
1631              setattr(spin, 'i0_err', {}) 
1632   
1633          # Do Grid Search 
1634          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=21, constraints=True, verbosity=1) 
1635   
1636          # Start dic. 
1637          my_dic = {} 
1638   
1639          # Define counter for maximum elements in the numpy array list 
1640          NE = 0 
1641          NS = 1 
1642          NM = 0 
1643          NO = 0 
1644          ND = 0 
1645          NT = 0 
1646   
1647          for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1648              # Save to counter. 
1649              if ei > NE: 
1650                  NE = ei 
1651              if mi > NM: 
1652                  NM = mi 
1653              if oi > NO: 
1654                  NO = oi 
1655              if di > ND: 
1656                 ND = di 
1657   
1658              for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1659                  # Save to counter. 
1660                  if ti > NT: 
1661                      NT = ti 
1662   
1663          # Add 1 to counter, since index start from 0. 
1664          NE = NE + 1 
1665          NM = NM + 1  
1666          NO = NO + 1 
1667          ND = ND + 1 
1668          NT = NT + 1 
1669   
1670          # Make data array. 
1671          values_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1672          errors_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1673          times_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1674          struct_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1675          param_key_list = [] 
1676   
1677   
1678          # Loop over each spectrometer frequency and dispersion point. 
1679          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1680              # Add key to dic. 
1681              my_dic[spin_id] = {} 
1682   
1683              # Generate spin string. 
1684              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1685   
1686              # Loop over the parameters. 
1687              #print("Grid optimised parameters for spin: %s" % (spin_string)) 
1688   
1689              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1690                  # Generate the param_key. 
1691                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1692   
1693                  # Append key. 
1694                  param_key_list.append(param_key) 
1695   
1696                  # Add key to dic. 
1697                  my_dic[spin_id][param_key] = {} 
1698   
1699                  # Get the value. 
1700                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1701                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1702   
1703                  # Save to dic. 
1704                  my_dic[spin_id][param_key]['R2eff_value_grid'] = R2eff_value 
1705                  my_dic[spin_id][param_key]['i0_value_grid'] = i0_value 
1706   
1707                  ## Now try do a line of best fit by least squares. 
1708                  # The peak intensities, errors and times. 
1709                  values = [] 
1710                  errors = [] 
1711                  times = [] 
1712                  for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1713                      value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1714                      values.append(value) 
1715   
1716                      error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1717                      errors.append(error) 
1718                      times.append(time) 
1719   
1720                      # Save to numpy arrays. 
1721                      values_arr[ei, 0, mi, oi, di, ti] = value 
1722                      errors_arr[ei, 0, mi, oi, di, ti] = error 
1723                      times_arr[ei, 0, mi, oi, di, ti] = time 
1724                      struct_arr[ei, 0, mi, oi, di, ti] = 1.0 
1725   
1726                  # y= A exp(x * k) 
1727                  # w[i] = ln(y[i]) 
1728                  # int[i] = i0 * exp( - times[i] * r2eff); 
1729                  w = log(array(values)) 
1730                  x = - array(times) 
1731                  n = len(times) 
1732   
1733                  b = (sum(x*w) - 1./n * sum(x) * sum(w) ) / ( sum(x**2) - 1./n * (sum(x))**2 ) 
1734                  a = 1./n * sum(w) - b * 1./n * sum(x) 
1735                  R2eff_est = b 
1736                  i0_est = exp(a) 
1737   
1738                  my_dic[spin_id][param_key]['R2eff_est'] = R2eff_est 
1739                  my_dic[spin_id][param_key]['i0_est'] = i0_est 
1740   
1741                  # Print value. 
1742                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1743                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1744   
1745   
1746          # Do minimisation. 
1747          set_func_tol = 1e-25 
1748          set_max_iter = int(1e7) 
1749          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1750   
1751          # Loop over each spectrometer frequency and dispersion point. 
1752          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1753              # Generate spin string. 
1754              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1755   
1756              # Loop over the parameters. 
1757              print("Optimised parameters for spin: %s" % (spin_string)) 
1758   
1759              for exp_type, frq, offset, point in loop_exp_frq_offset_point(): 
1760                  # Generate the param_key. 
1761                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1762   
1763                  # Get the value. 
1764                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1765                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1766   
1767                  # Extract from dic. 
1768                  R2eff_value_grid = my_dic[spin_id][param_key]['R2eff_value_grid'] 
1769                  i0_value_grid = my_dic[spin_id][param_key]['i0_value_grid'] 
1770                  R2eff_est = my_dic[spin_id][param_key]['R2eff_est'] 
1771                  i0_est = my_dic[spin_id][param_key]['i0_est'] 
1772   
1773                  # Print value. 
1774                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1775                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1776   
1777                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'R2eff', "Grid : Min : Estimated:", R2eff_value_grid, R2eff_value, R2eff_est)) 
1778                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'i0', "Grid : Min : Estimated:", i0_value_grid, i0_value, i0_est)) 
1779   
1780          print(NE, NS, NM, NO, ND, NT) 
1781          for param_key in param_key_list: 
1782              print("        '%s'," % param_key) 
1783          print(values_arr.shape) 
1784   
1785          # Save arrays to profiling. 
1786          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep 
1787          #save(data_path + "values_arr", values_arr) 
1788          #save(data_path + "errors_arr", errors_arr) 
1789          #save(data_path + "times_arr", times_arr) 
1790          #save(data_path + "struct_arr", struct_arr) 
1791   
1792   
1793 -    def test_bug_atul_srivastava(self): 
1794          """Test data from Atul Srivastava.  This is a bug missing raising a Relax Error, since the setup points to a situation where the data 
1795          shows it is exponential fitting, but only one time point is added per file. 
1796   
1797          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1718>}: 
1798          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735>}: 
1799          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735/focus=1736>}: 
1800   
1801          """ 
1802   
1803          # Data path. 
1804          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_Atul_Srivastava' 
1805          file = data_path + sep + 'bug_script.py' 
1806   
1807          # Run script. 
1808          self.interpreter.script(file=file, dir=None) 
1809   
1810          # The grid search size (the number of increments per dimension). 
1811          GRID_INC = 11 
1812   
1813          # Check-data. 
1814          ################# 
1815   
1816          # Loop over spins, to see current setup. 
1817          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1818              print(mol_name, resi, resn, spin_id) 
1819   
1820          # Loop over setup. 
1821          for id in cdp.exp_type: 
1822              print(id, cdp.exp_type[id], cdp.spectrometer_frq[id], cdp.spin_lock_offset[id], cdp.spin_lock_nu1[id]) 
1823   
1824   
1825          # Manual minimisation. 
1826          ################# 
1827          if True: 
1828              # Set the model. 
1829              self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
1830   
1831              # Check if intensity errors have already been calculated. 
1832              check_intensity_errors() 
1833   
1834              # Calculate the R2eff values for the fixed relaxation time period data types. 
1835              if cdp.model_type == MODEL_R2EFF and not has_exponential_exp_type(): 
1836                  self.interpreter.minimise.calculate() 
1837   
1838              # Optimise the model. 
1839              else: 
1840                  constraints = False 
1841                  min_algor = 'Newton' 
1842                  self.assertRaises(RelaxError, self.interpreter.minimise.grid_search, inc=GRID_INC) 
1843                  self.assertRaises(RelaxError, self.interpreter.minimise.execute, min_algor=min_algor, constraints=constraints) 
1844   
1845          # Inspect. 
1846          if False: 
1847              # Loop over attributes. 
1848              par_attr_list = ['r2eff', 'i0'] 
1849   
1850              # Collect the estimation data. 
1851              my_dic = {} 
1852              param_key_list = [] 
1853              est_keys = [] 
1854              est_key = 'grid' 
1855              est_keys.append(est_key) 
1856              spin_id_list = [] 
1857   
1858              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1859                  # Add key to dic. 
1860                  my_dic[spin_id] = {} 
1861   
1862                  # Add key for estimate. 
1863                  my_dic[spin_id][est_key] = {} 
1864   
1865                  # Add spin key to list. 
1866                  spin_id_list.append(spin_id) 
1867   
1868                  # Generate spin string. 
1869                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1870   
1871                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1872                      # Generate the param_key. 
1873                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1874                      #param_key = generate_r20_key(exp_type=exp_type, frq=frq) 
1875   
1876                      # Append key. 
1877                      param_key_list.append(param_key) 
1878   
1879                      # Add key to dic. 
1880                      my_dic[spin_id][est_key][param_key] = {} 
1881   
1882                      # Get the value. 
1883                      # Loop over err attributes. 
1884                      for par_attr in par_attr_list: 
1885                          if hasattr(cur_spin, par_attr): 
1886                              get_par_attr = getattr(cur_spin, par_attr)[param_key] 
1887                          else: 
1888                              get_par_attr = 0.0 
1889   
1890                          # Save to dic. 
1891                          my_dic[spin_id][est_key][param_key][par_attr] = get_par_attr 
1892   
1893                      # Check number of values. 
1894                      values = [] 
1895                      errors = [] 
1896                      times = [] 
1897                      for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1898                          value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1899                          values.append(value) 
1900   
1901                          error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1902                          errors.append(error) 
1903                          times.append(time) 
1904   
1905                      # Save to dic. 
1906                      my_dic[spin_id][est_key][param_key]['values'] = values 
1907                      my_dic[spin_id][est_key][param_key]['errors'] = errors 
1908                      my_dic[spin_id][est_key][param_key]['times'] = times 
1909   
1910          # Analysis variables. 
1911          ##################### 
1912   
1913          # The dispersion models. 
1914          MODELS = ['R2eff', 'No Rex'] 
1915   
1916          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
1917          MC_NUM = 10 
1918   
1919          # A flag which if True will activate Monte Carlo simulations for all models.  Note this will hugely increase the computation time. 
1920          MC_SIM_ALL_MODELS = False 
1921   
1922          # The results directory. 
1923          RESULTS_DIR = ds.tmpdir 
1924   
1925          # The directory of results of an earlier analysis without clustering. 
1926          PRE_RUN_DIR = None 
1927   
1928          # The model selection technique to use. 
1929          MODSEL = 'AIC' 
1930   
1931          # The flag for only using numeric models in the final model selection. 
1932          NUMERIC_ONLY = False 
1933   
1934          # The R1rho value in rad/s by which to judge insignificance.  If the maximum difference between two points on all dispersion curves for a spin is less than this value, that spin will be deselected. 
1935          INSIGNIFICANCE = 1.0 
1936   
1937          # Auto-analysis execution. 
1938          self.assertRaises(RelaxError, relax_disp.Relax_disp, pipe_name='relax_disp', results_dir=RESULTS_DIR, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, insignificance=INSIGNIFICANCE, numeric_only=NUMERIC_ONLY) 
1939   
1940   
1941 -    def test_bug_negative_intensities_cpmg(self): 
1942          """Test data, where peak intensities are negative in CPMG 
1943   
1944          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
1945          """ 
1946   
1947          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'bug_neg_int_acbp_cpmg_disp_048MGuHCl_40C_041223' 
1948   
1949          # Create the spins 
1950          self.interpreter.spectrum.read_spins(file="peaks_list_max_standard.ser", dir=data_path) 
1951   
1952          # Name the isotope for field strength scaling. 
1953          self.interpreter.spin.isotope(isotope='15N') 
1954   
1955          # Read the spectrum from NMRSeriesTab file. The "auto" will generate spectrum name of form: Z_A{i} 
1956          self.interpreter.spectrum.read_intensities(file="peaks_list_max_standard.ser", dir=data_path, spectrum_id='auto', int_method='height') 
1957   
1958          # Loop over the spectra settings. 
1959          ncycfile=open(data_path + sep + 'ncyc.txt', 'r') 
1960   
1961          # Make empty ncyclist 
1962          ncyclist = [] 
1963   
1964          i = 0 
1965          for line in ncycfile: 
1966              ncyc = line.split()[0] 
1967              time_T2 = float(line.split()[1]) 
1968              vcpmg = line.split()[2] 
1969              set_sfrq = float(line.split()[3]) 
1970              rmsd_err = float(line.split()[4]) 
1971   
1972              # Test if spectrum is a reference 
1973              if float(vcpmg) == 0.0: 
1974                  vcpmg = None 
1975              else: 
1976                  vcpmg = round(float(vcpmg), 3) 
1977   
1978              # Add ncyc to list 
1979              ncyclist.append(int(ncyc)) 
1980   
1981              # Set the current spectrum id 
1982              current_id = "Z_A%s"%(i) 
1983   
1984              # Set the current experiment type. 
1985              self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
1986   
1987              # Set the peak intensity errors, as defined as the baseplane RMSD. 
1988              self.interpreter.spectrum.baseplane_rmsd(error=rmsd_err, spectrum_id=current_id) 
1989   
1990              # Set the NMR field strength of the spectrum. 
1991              self.interpreter.spectrometer.frequency(id=current_id, frq=set_sfrq, units='MHz') 
1992   
1993              # Relaxation dispersion CPMG constant time delay T (in s). 
1994              self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
1995   
1996              # Set the relaxation dispersion CPMG frequencies. 
1997              self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
1998   
1999              i += 1 
2000   
2001          # Specify the duplicated spectra. 
2002          self.interpreter.spectrum.replicated(spectrum_ids=['Z_A1', 'Z_A15']) 
2003   
2004          # Delete replicate spectrum 
2005          #self.interpreter.spectrum.delete('Z_A15') 
2006   
2007          MODELS = [MODEL_R2EFF, MODEL_NOREX] 
2008          GRID_INC = 5; MC_NUM = 3; MODSEL = 'AIC' 
2009   
2010          results_dir = ds.tmpdir 
2011   
2012          # Execute 
2013          relax_disp.Relax_disp(pipe_name='relax_disp', results_dir=results_dir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
2014   
2015          # Check spin less R2eff points. 
2016          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
2017              # Assert that spin 4, has one less R2eff point, since one of the intensities are negative. 
2018              if spin_id == ':4@N': 
2019                  self.assertEqual(len(cur_spin.r2eff), 14) 
2020              else: 
2021                  self.assertEqual(len(cur_spin.r2eff), 15) 
2022   
2023   
2024 -    def test_check_missing_r1(self): 
2025          """Test of the check_missing_r1() function.""" 
2026   
2027          # Set up some spins. 
2028          self.setup_missing_r1_spins() 
2029   
2030          # Set variables. 
2031          exp_type = 'R1rho' 
2032          frq = 800.1 * 1E6 
2033   
2034          spectrum_id='test' 
2035   
2036          # Set an experiment type to the pipe. 
2037          self.interpreter.relax_disp.exp_type(spectrum_id=spectrum_id, exp_type=exp_type) 
2038   
2039          # Set a frequency to loop through. 
2040          self.interpreter.spectrometer.frequency(id=spectrum_id, frq=frq, units='Hz') 
2041   
2042          # Check R1 for DPL94. 
2043          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
2044          self.assertEqual(check_missing_r1_return, True) 
2045   
2046          # Check R1 for R2eff. 
2047          check_missing_r1_return = check_missing_r1(model=MODEL_R2EFF) 
2048          self.assertEqual(check_missing_r1_return, False) 
2049   
2050          # The path to the data files. 
2051          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
2052   
2053          # Now load some R1 data. 
2054          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
2055   
2056          # Check R1. 
2057          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
2058          self.assertEqual(check_missing_r1_return, False) 
2059   
2060   
2061 -    def test_cpmg_synthetic_b14_to_ns3d_cluster(self): 
2062          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site 3D, for clustered analysis. 
2063   
2064          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2065   
2066          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2067          """ 
2068   
2069          # Reset. 
2070          #self.interpreter.reset() 
2071   
2072          ## Set Experiments. 
2073          model_create = 'B14' 
2074          #model_create = 'NS CPMG 2-site expanded' 
2075          model_analyse = 'NS CPMG 2-site 3D' 
2076   
2077          # Exp 1 
2078          sfrq_1 = 599.8908617*1E6 
2079          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2080          time_T2_1 = 0.06 
2081          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2082          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2083          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2084          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2085   
2086          sfrq_2 = 499.8908617*1E6 
2087          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2088          time_T2_2 = 0.05 
2089          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2090          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2091          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2092          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2093   
2094          # Collect all exps 
2095          exps = [exp_1, exp_2] 
2096   
2097          spins = [ 
2098              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2099              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2100              ] 
2101   
2102          # Collect the data to be used. 
2103          ds.data = [model_create, model_analyse, spins, exps] 
2104   
2105          # The tmp directory. None is the local directory. 
2106          ds.tmpdir = ds.tmpdir 
2107   
2108          # The results directory. None is the local directory. 
2109          #ds.resdir = None 
2110          ds.resdir = ds.tmpdir 
2111   
2112          # Do r20_from_min_r2eff ?. 
2113          ds.r20_from_min_r2eff = True 
2114   
2115          # Remove insignificant level. 
2116          ds.insignificance = 0.0 
2117   
2118          # The grid search size (the number of increments per dimension). 
2119          ds.GRID_INC = None 
2120   
2121          # The do clustering. 
2122          ds.do_cluster = True 
2123   
2124          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2125          # The default value is 1e-25. 
2126          ds.set_func_tol = 1e-1 
2127   
2128          # The maximum number of iterations. 
2129          # The default value is 1e7. 
2130          ds.set_max_iter = 1000 
2131   
2132          # The verbosity level. 
2133          ds.verbosity = 1 
2134   
2135          # The rel_change WARNING level. 
2136          ds.rel_change = 0.05 
2137   
2138          # The plot_curves. 
2139          ds.plot_curves = False 
2140   
2141          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2142          ds.sherekhan_input = False 
2143   
2144          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2145          ds.opendx = False 
2146   
2147          # The set r2eff err. 
2148          ds.r2eff_err = 0.1 
2149   
2150          # The print result info. 
2151          ds.print_res = True 
2152   
2153          # Execute the script. 
2154          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2155   
2156          cur_spins = ds.data[2] 
2157          # Compare results. 
2158          for i in range(len(cur_spins)): 
2159              res_name, res_num, spin_name, params = cur_spins[i] 
2160              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2161              cur_spin = return_spin(cur_spin_id) 
2162   
2163              grid_params = ds.grid_results[i][3] 
2164   
2165              # Extract the clust results. 
2166              min_params = ds.clust_results[i][3] 
2167              # Now read the parameters. 
2168              print("For spin: '%s'"%cur_spin_id) 
2169              for mo_param in cur_spin.params: 
2170                  # The R2 is a dictionary, depending on spectrometer frequency. 
2171                  if isinstance(getattr(cur_spin, mo_param), dict): 
2172                      grid_r2 = grid_params[mo_param] 
2173                      min_r2 = min_params[mo_param] 
2174                      set_r2 = params[mo_param] 
2175                      for key, val in list(set_r2.items()): 
2176                          grid_r2_frq = grid_r2[key] 
2177                          min_r2_frq = min_r2[key] 
2178                          set_r2_frq = set_r2[key] 
2179                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2180                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2181                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2182                          if rel_change > ds.rel_change: 
2183                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2184                              print("###################################") 
2185   
2186                          ## Make test on R2. 
2187                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2188                  else: 
2189                      grid_val = grid_params[mo_param] 
2190                      min_val = min_params[mo_param] 
2191                      set_val = params[mo_param] 
2192                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2193                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2194                      if rel_change > ds.rel_change: 
2195                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2196                          print("###################################") 
2197   
2198                      ## Make test on parameters. 
2199                      if mo_param == 'dw': 
2200                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2201                      elif mo_param == 'kex': 
2202                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2203                      elif mo_param == 'pA': 
2204                          self.assertAlmostEqual(set_val, min_val, 2) 
2205   
2206   
2207 -    def test_cpmg_synthetic_b14_to_ns_star_cluster(self): 
2208          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site STAR, for clustered analysis. 
2209   
2210          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2211   
2212          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2213          """ 
2214   
2215          # Reset. 
2216          #self.interpreter.reset() 
2217   
2218          ## Set Experiments. 
2219          model_create = 'B14' 
2220          #model_create = 'NS CPMG 2-site expanded' 
2221          model_analyse = 'NS CPMG 2-site star' 
2222   
2223          # Exp 1 
2224          sfrq_1 = 599.8908617*1E6 
2225          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2226          time_T2_1 = 0.06 
2227          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2228          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2229          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2230          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2231   
2232          sfrq_2 = 499.8908617*1E6 
2233          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2234          time_T2_2 = 0.05 
2235          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2236          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2237          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2238          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2239   
2240          # Collect all exps 
2241          exps = [exp_1, exp_2] 
2242   
2243          spins = [ 
2244              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2245              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2246              ] 
2247   
2248          # Collect the data to be used. 
2249          ds.data = [model_create, model_analyse, spins, exps] 
2250   
2251          # The tmp directory. None is the local directory. 
2252          ds.tmpdir = ds.tmpdir 
2253   
2254          # The results directory. None is the local directory. 
2255          #ds.resdir = None 
2256          ds.resdir = ds.tmpdir 
2257   
2258          # Do r20_from_min_r2eff ?. 
2259          ds.r20_from_min_r2eff = True 
2260   
2261          # Remove insignificant level. 
2262          ds.insignificance = 0.0 
2263   
2264          # The grid search size (the number of increments per dimension). 
2265          ds.GRID_INC = None 
2266   
2267          # The do clustering. 
2268          ds.do_cluster = True 
2269   
2270          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2271          # The default value is 1e-25. 
2272          ds.set_func_tol = 1e-1 
2273   
2274          # The maximum number of iterations. 
2275          # The default value is 1e7. 
2276          ds.set_max_iter = 1000 
2277   
2278          # The verbosity level. 
2279          ds.verbosity = 1 
2280   
2281          # The rel_change WARNING level. 
2282          ds.rel_change = 0.05 
2283   
2284          # The plot_curves. 
2285          ds.plot_curves = False 
2286   
2287          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2288          ds.sherekhan_input = False 
2289   
2290          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2291          ds.opendx = False 
2292   
2293          # The set r2eff err. 
2294          ds.r2eff_err = 0.1 
2295   
2296          # The print result info. 
2297          ds.print_res = True 
2298   
2299          # Execute the script. 
2300          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2301   
2302          cur_spins = ds.data[2] 
2303          # Compare results. 
2304          for i in range(len(cur_spins)): 
2305              res_name, res_num, spin_name, params = cur_spins[i] 
2306              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2307              cur_spin = return_spin(cur_spin_id) 
2308   
2309              grid_params = ds.grid_results[i][3] 
2310   
2311              # Extract the clust results. 
2312              min_params = ds.clust_results[i][3] 
2313              # Now read the parameters. 
2314              print("For spin: '%s'"%cur_spin_id) 
2315              for mo_param in cur_spin.params: 
2316                  # The R2 is a dictionary, depending on spectrometer frequency. 
2317                  if isinstance(getattr(cur_spin, mo_param), dict): 
2318                      grid_r2 = grid_params[mo_param] 
2319                      min_r2 = min_params[mo_param] 
2320                      set_r2 = params[mo_param] 
2321                      for key, val in list(set_r2.items()): 
2322                          grid_r2_frq = grid_r2[key] 
2323                          min_r2_frq = min_r2[key] 
2324                          set_r2_frq = set_r2[key] 
2325                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2326                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2327                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2328                          if rel_change > ds.rel_change: 
2329                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2330                              print("###################################") 
2331   
2332                          ## Make test on R2. 
2333                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2334                  else: 
2335                      grid_val = grid_params[mo_param] 
2336                      min_val = min_params[mo_param] 
2337                      set_val = params[mo_param] 
2338                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2339                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2340                      if rel_change > ds.rel_change: 
2341                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2342                          print("###################################") 
2343   
2344                      ## Make test on parameters. 
2345                      if mo_param == 'dw': 
2346                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2347                      elif mo_param == 'kex': 
2348                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2349                      elif mo_param == 'pA': 
2350                          self.assertAlmostEqual(set_val, min_val, 2) 
2351   
2352   
2353 -    def test_cpmg_synthetic_ns3d_to_cr72(self): 
2354          """Test synthetic cpmg data. 
2355   
2356          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with CR72. 
2357          """ 
2358   
2359          # Reset. 
2360          #self.interpreter.reset() 
2361   
2362          ## Set Experiments. 
2363          model_create = 'NS CPMG 2-site 3D' 
2364          #model_create = 'NS CPMG 2-site expanded' 
2365          model_analyse = 'CR72' 
2366          # Exp 1 
2367          sfrq_1 = 599.8908617*1E6 
2368          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2369          time_T2_1 = 0.06 
2370          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2371          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2372          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2373   
2374          sfrq_2 = 499.8908617*1E6 
2375          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2376          time_T2_2 = 0.05 
2377          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2378          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2379          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2380   
2381          # Collect all exps 
2382          exps = [exp_1, exp_2] 
2383   
2384          spins = [ 
2385              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2386              ] 
2387   
2388          # Collect the data to be used. 
2389          ds.data = [model_create, model_analyse, spins, exps] 
2390   
2391          # The tmp directory. None is the local directory. 
2392          ds.tmpdir = ds.tmpdir 
2393   
2394          # The results directory. None is the local directory. 
2395          #ds.resdir = None 
2396          ds.resdir = ds.tmpdir 
2397   
2398          # Do r20_from_min_r2eff ?. 
2399          ds.r20_from_min_r2eff = True 
2400   
2401          # Remove insignificant level. 
2402          ds.insignificance = 0.0 
2403   
2404          # The grid search size (the number of increments per dimension). 
2405          ds.GRID_INC = 8 
2406   
2407          # The do clustering. 
2408          ds.do_cluster = False 
2409   
2410          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2411          # The default value is 1e-25. 
2412          ds.set_func_tol = 1e-9 
2413   
2414          # The maximum number of iterations. 
2415          # The default value is 1e7. 
2416          ds.set_max_iter = 1000 
2417   
2418          # The verbosity level. 
2419          ds.verbosity = 1 
2420   
2421          # The rel_change WARNING level. 
2422          ds.rel_change = 0.05 
2423   
2424          # The plot_curves. 
2425          ds.plot_curves = False 
2426   
2427          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2428          ds.sherekhan_input = False 
2429   
2430          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2431          ds.opendx = False 
2432   
2433          # The set r2eff err. 
2434          ds.r2eff_err = 0.1 
2435   
2436          # The print result info. 
2437          ds.print_res = False 
2438   
2439          # Execute the script. 
2440          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2441   
2442          cur_spins = ds.data[2] 
2443          # Compare results. 
2444          for i in range(len(cur_spins)): 
2445              res_name, res_num, spin_name, params = cur_spins[i] 
2446              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2447              cur_spin = return_spin(cur_spin_id) 
2448   
2449              grid_params = ds.grid_results[i][3] 
2450              min_params = ds.min_results[i][3] 
2451              # Now read the parameters. 
2452              print("For spin: '%s'"%cur_spin_id) 
2453              for mo_param in cur_spin.params: 
2454                  # The R2 is a dictionary, depending on spectrometer frequency. 
2455                  if isinstance(getattr(cur_spin, mo_param), dict): 
2456                      grid_r2 = grid_params[mo_param] 
2457                      min_r2 = min_params[mo_param] 
2458                      set_r2 = params[mo_param] 
2459                      for key, val in list(set_r2.items()): 
2460                          grid_r2_frq = grid_r2[key] 
2461                          min_r2_frq = min_r2[key] 
2462                          set_r2_frq = set_r2[key] 
2463                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2464                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2465                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2466                          if rel_change > ds.rel_change: 
2467                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2468                              print("###################################") 
2469   
2470                          ## Make test on R2. 
2471                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2472                  else: 
2473                      grid_val = grid_params[mo_param] 
2474                      min_val = min_params[mo_param] 
2475                      set_val = params[mo_param] 
2476                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2477                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2478                      if rel_change > ds.rel_change: 
2479                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2480                          print("###################################") 
2481   
2482                      ## Make test on parameters. 
2483                      if mo_param == 'dw': 
2484                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2485                      elif mo_param == 'kex': 
2486                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2487                      elif mo_param == 'pA': 
2488                          self.assertAlmostEqual(set_val, min_val, 3) 
2489   
2490   
2491 -    def test_cpmg_synthetic_ns3d_to_b14(self): 
2492          """Test synthetic cpmg data. 
2493   
2494          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with B14. 
2495          Try to catch bug #22021 U{https://gna.org/bugs/index.php?22021}: Model B14 shows bad fitting to data. 
2496          """ 
2497   
2498          # Reset. 
2499          #self.interpreter.reset() 
2500   
2501          ## Set Experiments. 
2502          model_create = 'NS CPMG 2-site 3D' 
2503          #model_create = 'NS CPMG 2-site expanded' 
2504          model_analyse = 'B14' 
2505          # Exp 1 
2506          sfrq_1 = 599.8908617*1E6 
2507          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2508          time_T2_1 = 0.06 
2509          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2510          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2511          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2512   
2513          sfrq_2 = 499.8908617*1E6 
2514          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2515          time_T2_2 = 0.05 
2516          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2517          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2518          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2519   
2520          # Collect all exps 
2521          exps = [exp_1, exp_2] 
2522   
2523          spins = [ 
2524              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2525              ] 
2526   
2527          # Collect the data to be used. 
2528          ds.data = [model_create, model_analyse, spins, exps] 
2529   
2530          # The tmp directory. None is the local directory. 
2531          ds.tmpdir = ds.tmpdir 
2532   
2533          # The results directory. None is the local directory. 
2534          #ds.resdir = None 
2535          ds.resdir = ds.tmpdir 
2536   
2537          # Do r20_from_min_r2eff ?. 
2538          ds.r20_from_min_r2eff = True 
2539   
2540          # Remove insignificant level. 
2541          ds.insignificance = 0.0 
2542   
2543          # The grid search size (the number of increments per dimension). 
2544          ds.GRID_INC = 8 
2545   
2546          # The do clustering. 
2547          ds.do_cluster = False 
2548   
2549          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2550          # The default value is 1e-25. 
2551          ds.set_func_tol = 1e-9 
2552   
2553          # The maximum number of iterations. 
2554          # The default value is 1e7. 
2555          ds.set_max_iter = 1000 
2556   
2557          # The verbosity level. 
2558          ds.verbosity = 1 
2559   
2560          # The rel_change WARNING level. 
2561          ds.rel_change = 0.05 
2562   
2563          # The plot_curves. 
2564          ds.plot_curves = False 
2565   
2566          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2567          ds.sherekhan_input = False 
2568   
2569          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2570          ds.opendx = False 
2571   
2572          # The set r2eff err. 
2573          ds.r2eff_err = 0.1 
2574   
2575          # The print result info. 
2576          ds.print_res = False 
2577   
2578          # Execute the script. 
2579          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2580   
2581          cur_spins = ds.data[2] 
2582          # Compare results. 
2583          for i in range(len(cur_spins)): 
2584              res_name, res_num, spin_name, params = cur_spins[i] 
2585              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2586              cur_spin = return_spin(cur_spin_id) 
2587   
2588              grid_params = ds.grid_results[i][3] 
2589              min_params = ds.min_results[i][3] 
2590              # Now read the parameters. 
2591              print("For spin: '%s'"%cur_spin_id) 
2592              for mo_param in cur_spin.params: 
2593                  # The R2 is a dictionary, depending on spectrometer frequency. 
2594                  if isinstance(getattr(cur_spin, mo_param), dict): 
2595                      grid_r2 = grid_params[mo_param] 
2596                      min_r2 = min_params[mo_param] 
2597                      set_r2 = params[mo_param] 
2598                      for key, val in list(set_r2.items()): 
2599                          grid_r2_frq = grid_r2[key] 
2600                          min_r2_frq = min_r2[key] 
2601                          set_r2_frq = set_r2[key] 
2602                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2603                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2604                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2605                          if rel_change > ds.rel_change: 
2606                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2607                              print("###################################") 
2608   
2609                          ## Make test on R2. 
2610                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2611                  else: 
2612                      grid_val = grid_params[mo_param] 
2613                      min_val = min_params[mo_param] 
2614                      set_val = params[mo_param] 
2615                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2616                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2617                      if rel_change > ds.rel_change: 
2618                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2619                          print("###################################") 
2620   
2621                      ## Make test on parameters. 
2622                      if mo_param == 'dw': 
2623                          self.assertAlmostEqual(set_val/10, min_val/10, 5) 
2624                      elif mo_param == 'kex': 
2625                          self.assertAlmostEqual(set_val/1000, min_val/1000, 5) 
2626                      elif mo_param == 'pA': 
2627                          self.assertAlmostEqual(set_val, min_val, 6) 
2628   
2629   
2630 -    def test_cpmg_synthetic_ns3d_to_cr72_noise_cluster(self): 
2631          """Test synthetic cpmg data. For CR72 with small noise and cluster. 
2632   
2633          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2634          """ 
2635   
2636          # Reset. 
2637          #self.interpreter.reset() 
2638   
2639          ## Set Experiments. 
2640          model_create = 'NS CPMG 2-site 3D' 
2641          #model_create = 'NS CPMG 2-site expanded' 
2642          model_analyse = 'CR72' 
2643   
2644          # Exp 1 
2645          sfrq_1 = 599.8908617*1E6 
2646          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2647          time_T2_1 = 0.06 
2648          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2649          r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2650          #r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2651          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2652   
2653          sfrq_2 = 499.8908617*1E6 
2654          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2655          time_T2_2 = 0.05 
2656          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2657          r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2658          #r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2659          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2660   
2661          # Collect all exps 
2662          exps = [exp_1, exp_2] 
2663   
2664          spins = [ 
2665              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ], 
2666              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.99, 'dw': 1.} ] 
2667              ] 
2668   
2669          # Collect the data to be used. 
2670          ds.data = [model_create, model_analyse, spins, exps] 
2671   
2672          # The tmp directory. None is the local directory. 
2673          ds.tmpdir = ds.tmpdir 
2674   
2675          # The results directory. None is the local directory. 
2676          #ds.resdir = None 
2677          ds.resdir = ds.tmpdir 
2678   
2679          # Do r20_from_min_r2eff ?. 
2680          ds.r20_from_min_r2eff = True 
2681   
2682          # Remove insignificant level. 
2683          ds.insignificance = 0.0 
2684   
2685          # The grid search size (the number of increments per dimension). 
2686          ds.GRID_INC = 13 
2687   
2688          # The do clustering. 
2689          ds.do_cluster = True 
2690   
2691          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2692          # The default value is 1e-25. 
2693          ds.set_func_tol = 1e-8 
2694   
2695          # The maximum number of iterations. 
2696          # The default value is 1e7. 
2697          ds.set_max_iter = 10000 
2698   
2699          # The verbosity level. 
2700          ds.verbosity = 1 
2701   
2702          # The rel_change WARNING level. 
2703          ds.rel_change = 0.05 
2704   
2705          # The plot_curves. 
2706          ds.plot_curves = False 
2707   
2708          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2709          ds.sherekhan_input = False 
2710   
2711          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2712          ds.opendx = False 
2713   
2714          # The set r2eff err. 
2715          ds.r2eff_err = 0.1 
2716   
2717          # The print result info. 
2718          ds.print_res = False 
2719   
2720          # Execute the script. 
2721          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2722   
2723          cur_spins = ds.data[2] 
2724          # Compare results. 
2725          for i in range(len(cur_spins)): 
2726              res_name, res_num, spin_name, params = cur_spins[i] 
2727              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2728              cur_spin = return_spin(cur_spin_id) 
2729   
2730              grid_params = ds.grid_results[i][3] 
2731   
2732              # Extract the clust results. 
2733              min_params = ds.clust_results[i][3] 
2734              # Now read the parameters. 
2735              print("For spin: '%s'"%cur_spin_id) 
2736              for mo_param in cur_spin.params: 
2737                  # The R2 is a dictionary, depending on spectrometer frequency. 
2738                  if isinstance(getattr(cur_spin, mo_param), dict): 
2739                      grid_r2 = grid_params[mo_param] 
2740                      min_r2 = min_params[mo_param] 
2741                      set_r2 = params[mo_param] 
2742                      for key, val in list(set_r2.items()): 
2743                          grid_r2_frq = grid_r2[key] 
2744                          min_r2_frq = min_r2[key] 
2745                          set_r2_frq = set_r2[key] 
2746                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2747                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2748                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2749                          if rel_change > ds.rel_change: 
2750                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2751                              print("###################################") 
2752   
2753                          ## Make test on R2. 
2754                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2755                  else: 
2756                      grid_val = grid_params[mo_param] 
2757                      min_val = min_params[mo_param] 
2758                      set_val = params[mo_param] 
2759                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2760                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2761                      if rel_change > ds.rel_change: 
2762                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2763                          print("###################################") 
2764   
2765                      ## Make test on parameters. 
2766                      if mo_param == 'dw': 
2767                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2768                      elif mo_param == 'kex': 
2769                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2770                      elif mo_param == 'pA': 
2771                          self.assertAlmostEqual(set_val, min_val, 2) 
2772   
2773   
2774 -    def test_cpmg_synthetic_dx_map_points(self): 
2775          """Test synthetic cpmg data, calling the dx.map function with one or two points. 
2776   
2777          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2778          """ 
2779   
2780          # Reset. 
2781          #self.interpreter.reset() 
2782   
2783          ## Set Experiments. 
2784          model_create = MODEL_NS_CPMG_2SITE_EXPANDED 
2785          model_analyse = 'CR72' 
2786          # Exp 1 
2787          sfrq_1 = 599.8908617*1E6 
2788          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2789          time_T2_1 = 0.06 
2790          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2791          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2792          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2793   
2794          sfrq_2 = 499.8908617*1E6 
2795          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2796          time_T2_2 = 0.05 
2797          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2798          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2799          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2800   
2801          # Collect all exps 
2802          exps = [exp_1, exp_2] 
2803   
2804          spins = [ 
2805              ['Ala', 1, 'N', {'r2': {r20_key_1:2, r20_key_2:2}, 'r2a': {r20_key_1:2, r20_key_2:2}, 'r2b': {r20_key_1:2, r20_key_2:2}, 'kex': 1000, 'pA': 0.99, 'dw': 2} ] 
2806              ] 
2807   
2808          # Collect the data to be used. 
2809          ds.data = [model_create, model_analyse, spins, exps] 
2810   
2811          # The tmp directory. None is the local directory. 
2812          ds.tmpdir = ds.tmpdir 
2813   
2814          # The results directory. None is the local directory. 
2815          #ds.resdir = None 
2816          ds.resdir = ds.tmpdir 
2817   
2818          # Do r20_from_min_r2eff ?. 
2819          ds.r20_from_min_r2eff = True 
2820   
2821          # Remove insignificant level. 
2822          ds.insignificance = 0.0 
2823   
2824          # The grid search size (the number of increments per dimension). 
2825          ds.GRID_INC = None 
2826   
2827          # The do clustering. 
2828          ds.do_cluster = False 
2829   
2830          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2831          # The default value is 1e-25. 
2832          ds.set_func_tol = 1e-9 
2833   
2834          # The maximum number of iterations. 
2835          # The default value is 1e7. 
2836          ds.set_max_iter = 1000 
2837   
2838          # The verbosity level. 
2839          ds.verbosity = 1 
2840   
2841          # The rel_change WARNING level. 
2842          ds.rel_change = 0.05 
2843   
2844          # The plot_curves. 
2845          ds.plot_curves = False 
2846   
2847          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2848          ds.sherekhan_input = False 
2849   
2850          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2851          ds.opendx = False 
2852   
2853          # The set r2eff err. 
2854          ds.r2eff_err = 0.1 
2855   
2856          # The print result info. 
2857          ds.print_res = False 
2858   
2859          # Execute the script. 
2860          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2861   
2862          # Get the spins. 
2863          cur_spins = ds.data[2] 
2864   
2865          # First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-) 
2866          ds.pipe_name_MODEL_MAP = "%s_%s_map"%(ds.pipe_name, model_analyse) 
2867          self.interpreter.pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL_MAP, bundle_to = ds.pipe_bundle) 
2868          self.interpreter.pipe.switch(pipe_name=ds.pipe_name_MODEL_MAP) 
2869   
2870          # Copy R2eff, but not the original parameters 
2871          self.interpreter.value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_MAP, param='r2eff') 
2872   
2873          # Then select model. 
2874          self.interpreter.relax_disp.select_model(model=model_analyse) 
2875   
2876          # Define dx.map settings. 
2877          ds.dx_inc = 4 
2878          ds.dx_params = ['dw', 'pA', 'kex'] 
2879   
2880          res_name, res_num, spin_name, params = cur_spins[0] 
2881          cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2882          cur_spin = return_spin(cur_spin_id) 
2883   
2884          print("Params for dx map is") 
2885          print(ds.dx_params) 
2886          print("Point param for dx map is") 
2887          print(ds.dx_set_val) 
2888          cur_model = model_analyse.replace(' ', '_') 
2889          file_name_map = "%s_map%s" % (cur_model, cur_spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
2890          file_name_point = "%s_point%s" % (cur_model, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
2891          self.interpreter.dx.map(params=ds.dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=10, file_prefix=file_name_map, dir=ds.resdir, point=[ds.dx_set_val, ds.dx_clust_val], point_file=file_name_point, create_par_file=True) 
2892   
2893          ## Check for file creation 
2894          # Set filepaths. 
2895          map_cfg = ds.tmpdir+sep+file_name_map+".cfg" 
2896          map_net = ds.tmpdir+sep+file_name_map+".net" 
2897          map_general = ds.tmpdir+sep+file_name_map+".general" 
2898          map_par = get_file_path(file_name=file_name_map+".par", dir=ds.tmpdir) 
2899          map_plot = get_file_path(file_name=file_name_map+".py", dir=ds.tmpdir) 
2900   
2901          point_general = ds.tmpdir+sep+file_name_point+".general" 
2902          point_point = ds.tmpdir+sep+file_name_point 
2903          point_par = get_file_path(file_name=file_name_point+".par", dir=ds.tmpdir) 
2904   
2905          # Test the files exists. 
2906          self.assert_(access(map_cfg, F_OK)) 
2907          self.assert_(access(map_net, F_OK)) 
2908          self.assert_(access(map_general, F_OK)) 
2909          self.assert_(access(map_par, F_OK)) 
2910          self.assert_(access(map_plot, F_OK)) 
2911          self.assert_(access(point_general, F_OK)) 
2912          self.assert_(access(point_point, F_OK)) 
2913          self.assert_(access(point_par, F_OK)) 
2914   
2915          # Open the files for testing. 
2916          # Check the cfg file. 
2917          print("\nChecking the dx map .cfg file.") 
2918          res_file = [ 
2919              '//'+"\n", 
2920              '//'+"\n", 
2921              '// time: Thu May  8 18:55:31 2014'+"\n", 
2922              '//'+"\n", 
2923              '// version: 3.2.0 (format), 4.3.2 (DX)'+"\n", 
2924              '//'+"\n", 
2925              '//'+"\n", 
2926              '// panel[0]: position = (0.0164,0.0000), size = 0.2521x0.1933, startup = 1, devstyle = 1'+"\n", 
2927              '// title: value = Control Panel'+"\n", 
2928              '//'+"\n", 
2929              '// workspace: width = 251, height = 142'+"\n", 
2930              '// layout: snap = 0, width = 50, height = 50, align = NN'+"\n", 
2931              '//'+"\n", 
2932              '// interactor Selector[1]: num_components = 1, value = 1 '+"\n", 
2933              '// selections: maximum = 2, current = 0 '+"\n", 
2934              '// option[0]: name = "Colour", value = 1'+"\n", 
2935              '// option[1]: name = "Grey", value = 2'+"\n", 
2936              '// instance: panel = 0, x = 81, y = 6, style = Scrolled List, vertical = 1, size = 170x136'+"\n", 
2937              '// label: value = Colour Selector'+"\n", 
2938              '//'+"\n", 
2939              '// node Image[3]:'+"\n", 
2940              '// title: value = Surface'+"\n", 
2941              '// depth: value = 24'+"\n", 
2942              '// window: position = (0.0000,0.0400), size = 0.9929x0.9276'+"\n", 
2943          ] 
2944          file = open(map_cfg, 'r') 
2945          lines = file.readlines() 
2946          file.close() 
2947          for i in range(len(res_file)): 
2948              # Skip time point 
2949              if i == 2: 
2950                  continue 
2951              self.assertEqual(res_file[i], lines[i]) 
2952   
2953          print("\nChecking the dx map .general file.") 
2954          res_file = [ 
2955              'file = CR72_map_1_N'+"\n", 
2956              'grid = 5 x 5 x 5'+"\n", 
2957              'format = ascii'+"\n", 
2958              'interleaving = field'+"\n", 
2959              'majority = row'+"\n", 
2960              'field = data'+"\n", 
2961              'structure = scalar'+"\n", 
2962              'type = float'+"\n", 
2963              'dependency = positions'+"\n", 
2964              'positions = regular, regular, regular, 0, 1, 0, 1, 0, 1'+"\n", 
2965              ''+"\n", 
2966              'end'+"\n", 
2967          ] 
2968          file = open(map_general, 'r') 
2969          lines = file.readlines() 
2970          file.close() 
2971          for i in range(len(res_file)): 
2972              # Skip time point 
2973              #if i == 2: 
2974              #    continue 
2975              self.assertEqual(res_file[i], lines[i]) 
2976   
2977          print("\nChecking the dx point .general file.") 
2978          res_file = [ 
2979              'file = CR72_point_1_N'+"\n", 
2980              'points = 2'+"\n", 
2981              'format = ascii'+"\n", 
2982              'interleaving = field'+"\n", 
2983              'field = locations, field0'+"\n", 
2984              'structure = 3-vector, scalar'+"\n", 
2985              'type = float, float'+"\n", 
2986              ''+"\n", 
2987              'end'+"\n", 
2988          ] 
2989          file = open(point_general, 'r') 
2990          lines = file.readlines() 
2991          file.close() 
2992          for i in range(len(res_file)): 
2993              # Skip time point 
2994              #if i == 2: 
2995              #    continue 
2996              self.assertEqual(res_file[i], lines[i]) 
2997   
2998          print("\nChecking the dx point point file.") 
2999          res_file = [ 
3000              '0.8            3.92           0.39964        1'+"\n", 
3001              '0.76981        3.9169         0.41353        1'+"\n", 
3002          ] 
3003          file = open(point_point, 'r') 
3004          lines = file.readlines() 
3005          file.close() 
3006          for i in range(len(res_file)): 
3007              # Skip time point 
3008              #if i == 2: 
3009              #    continue 
3010              self.assertEqual(res_file[i], lines[i]) 
3011   
3012          print("\nChecking the dx point par file.") 
3013          res_file = [ 
3014              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
3015              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
3016              '1      1.92453    0.98961    1034.72206    6396.02770    1         1.92453    0.98961    1034.72206    6396.02770    '+"\n", 
3017          ] 
3018          res_file2 = [ 
3019              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
3020              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
3021              '1      1.92452    0.98961    1034.72424    6396.02439    1         1.92452    0.98961    1034.72424    6396.02439    '+"\n", 
3022          ]  # Python 2.5 and 3.1. 
3023          file = open(point_par, 'r') 
3024          lines = file.readlines() 
3025          file.close() 
3026          for i in range(len(res_file)): 
3027              if lines[i] != res_file[i] and lines[i] != res_file2[i]: 
3028                  self.assertEqual(res_file[i], lines[i]) 
3029   
3030          print("\nChecking the matplotlib surface plot file.") 
3031          res_file = [ 
3032              'from copy import deepcopy'+"\n", 
3033              'import numpy as np'+"\n", 
3034              'import scipy.interpolate'+"\n", 
3035              'from numpy.ma import masked_where'+"\n", 
3036              ''+"\n", 
3037              'from mpl_toolkits.mplot3d import axes3d'+"\n", 
3038              'import matplotlib.pyplot as plt'+"\n", 
3039              'from matplotlib import cm'+"\n", 
3040              ''+"\n", 
3041              '# Open file and get header.'+"\n", 
3042              'mapfile_name = "%s.par"'%file_name_map+"\n", 
3043              'pointfile_name = "%s.par"'%file_name_point+"\n", 
3044              ''+"\n", 
3045          ] 
3046          file = open(map_plot, 'r') 
3047          lines = file.readlines() 
3048          file.close() 
3049          for i in range(len(res_file)): 
3050              self.assertEqual(res_file[i], lines[i]) 
3051   
3052   
3053 -    def test_curve_type_cpmg_fixed_time(self): 
3054          """Test the curve type detection using the Dr. Flemming Hansen's CPMG fixed time test data.""" 
3055   
3056          # Reset. 
3057          self.interpreter.reset() 
3058   
3059          # Load the base data. 
3060          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
3061          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3062   
3063          # The type. 
3064          curve_type = get_curve_type(id='500_133.33.in') 
3065          self.assertEqual(curve_type, 'fixed time') 
3066   
3067   
3068 -    def test_curve_type_r1rho_exponential(self, model=None): 
3069          """Test the curve type detection using the 'M61' exponential test data.""" 
3070   
3071          # Reset. 
3072          self.interpreter.reset() 
3073   
3074          # Load the base data. 
3075          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_on_res_m61' 
3076          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3077   
3078          # The type. 
3079          curve_type = get_curve_type(id='nu_2000_ncyc9') 
3080          self.assertEqual(curve_type, 'exponential') 
3081   
3082   
3083 -    def test_curve_type_r1rho_fixed_time(self, model=None): 
3084          """Test the curve type detection using the 'TP02' fixed time test data.""" 
3085   
3086          # Reset. 
3087          self.interpreter.reset() 
3088   
3089          # Load the base data. 
3090          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
3091          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3092   
3093          # The type. 
3094          curve_type = get_curve_type(id='nu_1000.0_500MHz') 
3095          self.assertEqual(curve_type, 'fixed time') 
3096   
3097   
3098 -    def test_dpl94_data_to_dpl94(self): 
3099          """Test the relaxation dispersion 'DPL94' model curve fitting to fixed time synthetic data.""" 
3100   
3101          # Fixed time variable. 
3102          ds.fixed = True 
3103   
3104          # Execute the script. 
3105          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_dpl94.py') 
3106   
3107          # The original parameters. 
3108          i0 = [100000.0, 20000.0] 
3109          r1rho_prime = [2.25, 24.0] 
3110          pA = 0.7 
3111          kex = 1000.0 
3112          delta_omega = [1.0, 2.0] 
3113          phi_ex = [] 
3114          for i in range(2): 
3115              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
3116   
3117          # Switch to the 'DPL94' model data pipe, then check for each spin. 
3118          self.interpreter.pipe.switch('DPL94 - relax_disp') 
3119          spin_index = 0 
3120          for spin, spin_id in spin_loop(return_id=True): 
3121              # Printout. 
3122              print("\nSpin %s." % spin_id) 
3123   
3124              # Check the fitted parameters. 
3125              self.assertAlmostEqual(spin.r2['R1rho - 800.00000000 MHz']/10, r1rho_prime[spin_index]/10, 2) 
3126              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
3127              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
3128   
3129              # Increment the spin index. 
3130              spin_index += 1 
3131   
3132   
3133 -    def test_dx_map_clustered(self): 
3134          """Test making dx_map for residues under clustered calculation. 
3135   
3136          This uses CPMG data from: 
3137              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE 
3138                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
3139                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, U{DOI 10.1002/prot.22886<http://dx.doi.org/10.1002/prot.22886>} 
3140          """ 
3141   
3142          # Define path to data  
3143          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
3144   
3145          # Read data. 
3146          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
3147   
3148          # Get residue of interest. 
3149          cur_spin_id = ":%i@%s"%(52, 'N') 
3150          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3151   
3152          # Get the spin container. 
3153          cur_spin = return_spin(cur_spin_id) 
3154   
3155          # Get the chi2 value 
3156          pre_chi2 = cur_spin.chi2 
3157   
3158          # Then do a local minimisation. 
3159          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3160          self.interpreter.minimise.calculate() 
3161   
3162          # Get the chi2 value after calculation. 
3163          calc_chi2 = cur_spin.chi2 
3164   
3165          # Assert calculation is equal. 
3166          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3167   
3168          # Define dx.map settings. 
3169          dx_inc = 2 
3170          dx_inc_sides = dx_inc / 2 
3171   
3172          dx_params = ['dw', 'pA', 'kex'] 
3173          dx_point_clustered_min = [cur_spin.dw, cur_spin.pA, cur_spin.kex] 
3174   
3175          print("Params for dx map is") 
3176          print(dx_params) 
3177          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3178          print(dx_point_clustered_min) 
3179   
3180          # Define file_names. 
3181          cur_model = 'CR72' 
3182          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3183          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3184   
3185          # Step-size of parameter is 10 % 
3186          param_delta = 0.1 
3187   
3188          # Determine bounds for lower and upper 
3189          lower = [] 
3190          upper = [] 
3191          for i, param_val in enumerate(dx_point_clustered_min): 
3192              param = dx_params[i] 
3193              step_val = param_delta * param_val 
3194              step_length = step_val * dx_inc_sides 
3195   
3196              # Calculate value 
3197              low_val = param_val - step_length 
3198              lower.append(low_val) 
3199   
3200              upp_val = param_val + step_length 
3201              upper.append(upp_val) 
3202   
3203              print("For param %s, lower=%3.3f, upper=%3.3f, step_value=%3.3f, steps=%i, centered at=%3.3f"% (param, low_val, upp_val, step_val, dx_inc, param_val)) 
3204   
3205          # If the number of increments are 2, there will be 3 point calculations per parameter. 
3206          # Since we have ordered the lower and upper limits on sides of the parameter, the middle index should give us the expected global value. 
3207          dx_param_indexes = dx_inc + 1 
3208          dx_point_index = dx_inc_sides + 1 
3209   
3210          # Find the line number. 
3211          line = 1 
3212          for i in range(1, dx_param_indexes + 1): 
3213              for j in range(1, dx_param_indexes + 1): 
3214                  for k in range(1, dx_param_indexes + 1): 
3215                      if i == dx_point_index and j == dx_point_index and k == dx_point_index: 
3216                          line_chi2 = line 
3217                      # Add to line counter. 
3218                      line += 1 
3219   
3220          # Define temporary folder. 
3221          result_dir = self.tmpdir 
3222   
3223          # For testing. 
3224          #result_dir = None 
3225          #lower = None 
3226          #upper = None 
3227          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3228   
3229   
3230          # Then do the map. 
3231          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point) 
3232   
3233          # Print where to locate values. 
3234          nr_chi2_val = dx_param_indexes**3 
3235          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3236          print("Global chi2=%3.3f, Calc_chi=%3.3f, map_line_chi2=%i" % (pre_chi2, calc_chi2, line_chi2) ) 
3237   
3238          ## Check for file creation 
3239          # Set filepaths. 
3240          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3241          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3242          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3243          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3244   
3245          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3246          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3247   
3248          # Test the files exists. 
3249          self.assert_(access(map_cfg, F_OK)) 
3250          self.assert_(access(map_net, F_OK)) 
3251          self.assert_(access(map_general, F_OK)) 
3252          self.assert_(access(point_general, F_OK)) 
3253          self.assert_(access(point_point, F_OK)) 
3254   
3255          # Open the file, and assert the chi2 value is as expected. 
3256          get_data = extract_data(file=map_name) 
3257   
3258          # Extract line 0, column 0. 
3259          test = float(get_data[line_chi2-1][0]) 
3260   
3261          # Assert. 
3262          self.assertAlmostEqual(test, pre_chi2,  6) 
3263   
3264   
3265 -    def test_dx_map_clustered_create_par_file(self): 
3266          """Test making dx_map for residues under clustered calculation, and the creation of the parameter file. 
3267   
3268          U{Task #7860<https://gna.org/task/index.php?7860>} : When dx_map is issued, create a parameter file which maps parameters to chi2 value. 
3269   
3270          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
3271          """ 
3272   
3273          # Define path to data  
3274          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'surface_chi2_clustered_fitting' 
3275   
3276          # Read data. 
3277          self.interpreter.results.read(prev_data_path + sep + 'coMDD_-_TSMFK01_-_min_-_32_-_free_spins.bz2') 
3278   
3279          # Get residue of interest. 
3280          cur_spin_id = ":%i@%s"%(65, 'N') 
3281          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3282   
3283          # Get the spin container. 
3284          cur_spin = return_spin(cur_spin_id) 
3285   
3286          # Get the chi2 value 
3287          pre_chi2 = cur_spin.chi2 
3288   
3289          # Then do a local minimisation. 
3290          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3291          self.interpreter.minimise.calculate() 
3292   
3293          # Get the chi2 value after calculation. 
3294          calc_chi2 = cur_spin.chi2 
3295   
3296          # Assert calculation is equal. 
3297          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3298   
3299          # Define dx.map settings. 
3300          dx_inc = 2 
3301          dx_params = ['dw', 'k_AB', 'r2a'] 
3302          dx_point_clustered_min = [cur_spin.dw, cur_spin.k_AB, cur_spin.r2a['SQ CPMG - 499.86214000 MHz']] 
3303   
3304          print("Params for dx map is") 
3305          print(dx_params) 
3306          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3307          print(dx_point_clustered_min) 
3308   
3309          # Define file_names. 
3310          cur_model = 'TSMFK01' 
3311          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3312          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3313   
3314          # Determine bounds for lower and upper 
3315          lower = [dx_point_clustered_min[0], dx_point_clustered_min[1], dx_point_clustered_min[2]] 
3316          upper = [19.0, 2.4, 9.5] 
3317   
3318          # Define temporary folder. 
3319          result_dir = self.tmpdir 
3320   
3321          # For testing. 
3322          #result_dir = None 
3323          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3324   
3325          # Then do the map. 
3326          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point, create_par_file=True) 
3327   
3328          # Print where to locate values. 
3329          nr_chi2_val = (dx_inc + 1)**3 
3330          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3331          print("Global chi2=%3.3f, Calc_chi=%3.3f" % (pre_chi2, calc_chi2) ) 
3332   
3333          ## Check for file creation 
3334          # Set filepaths. 
3335          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3336          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3337          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3338          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3339          map_par = get_file_path(file_name=file_name_map+".par", dir=result_dir) 
3340   
3341          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3342          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3343   
3344          # Test the files exists. 
3345          self.assert_(access(map_cfg, F_OK)) 
3346          self.assert_(access(map_net, F_OK)) 
3347          self.assert_(access(map_general, F_OK)) 
3348          self.assert_(access(map_par, F_OK)) 
3349          self.assert_(access(point_general, F_OK)) 
3350          self.assert_(access(point_point, F_OK)) 
3351   
3352          print("\nParams for dx map is") 
3353          print(dx_params) 
3354          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3355          print(dx_point_clustered_min, "\n") 
3356   
3357          # Open the parameter chi2 file, and assert the chi2 value in the sorted parameter file is not lower that than the global minimisation. 
3358          get_data = extract_data(file=map_par) 
3359   
3360          # Extract line 1, column 9. 
3361          test = float(get_data[1][9]) 
3362   
3363          # Print data if map contain a lower value than the global minimised value. 
3364          if test < pre_chi2: 
3365              print("\nInitial clustered minimised chi2 value is=%3.3f, whereby the minimum map value is=%3.3f\n" % (pre_chi2, test)) 
3366              for line in get_data: 
3367                  print(line) 
3368   
3369          # Assert that the initial global chi2 is lower than the map value. 
3370   
3371          # The following test was taken out, since this a particular interesting case. 
3372          # There exist a double minimum, where relax has not found the global minimum. 
3373          # This is due to not grid searching for R2A, but using the minimum  
3374          #self.assert_(pre_chi2 < test) 
3375   
3376   
3377 -    def test_estimate_r2eff_err(self): 
3378          """Test the user function for estimating R2eff errors from exponential curve fitting. 
3379   
3380          This follows Task 7822. 
3381          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3382   
3383          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3384          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3385          """ 
3386   
3387          # Cluster residues 
3388          cluster_ids = [ 
3389          ":13@N", 
3390          ":15@N", 
3391          ":16@N", 
3392          ":25@N", 
3393          ":26@N", 
3394          ":28@N", 
3395          ":39@N", 
3396          ":40@N", 
3397          ":41@N", 
3398          ":43@N", 
3399          ":44@N", 
3400          ":45@N", 
3401          ":49@N", 
3402          ":52@N", 
3403          ":53@N"] 
3404   
3405          # Load the data. 
3406          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3407   
3408          # The dispersion models. 
3409          MODELS = [MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3410   
3411          # The grid search size (the number of increments per dimension). 
3412          GRID_INC = None 
3413   
3414          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3415          MC_NUM = 3 
3416   
3417          # Model selection technique. 
3418          MODSEL = 'AIC' 
3419   
3420          # Execute the auto-analysis (fast). 
3421          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3422          OPT_FUNC_TOL = 1e-25 
3423          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3424          OPT_MAX_ITERATIONS = 10000000 
3425          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3426   
3427          result_dir_name = ds.tmpdir 
3428   
3429          # Make all spins free 
3430          for curspin in cluster_ids: 
3431              self.interpreter.relax_disp.cluster('free spins', curspin) 
3432              # Shut them down 
3433              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
3434   
3435          # Select only a subset of spins for global fitting 
3436          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3437          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3438   
3439          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3440          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3441   
3442          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3443          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3444   
3445          # Set the model. 
3446          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3447   
3448          # Check if intensity errors have already been calculated. 
3449          check_intensity_errors() 
3450   
3451          # Do a grid search. 
3452          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
3453   
3454          # Minimise. 
3455          self.interpreter.minimise.execute(min_algor='Newton', constraints=False, verbosity=1) 
3456   
3457          # Estimate R2eff errors. 
3458          self.interpreter.relax_disp.r2eff_err_estimate() 
3459   
3460          r1_fit = True 
3461   
3462          # Run the analysis. 
3463          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3464   
3465          # Verify the data. 
3466          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3467   
3468   
3469 -    def test_estimate_r2eff_err_auto(self): 
3470          """Test the user function for estimating R2eff errors from exponential curve fitting, via the auto_analyses menu. 
3471   
3472          This follows Task 7822. 
3473          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3474   
3475          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3476          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3477          """ 
3478   
3479          # Cluster residues 
3480          cluster_ids = [ 
3481          ":13@N", 
3482          ":15@N", 
3483          ":16@N", 
3484          ":25@N", 
3485          ":26@N", 
3486          ":28@N", 
3487          ":39@N", 
3488          ":40@N", 
3489          ":41@N", 
3490          ":43@N", 
3491          ":44@N", 
3492          ":45@N", 
3493          ":49@N", 
3494          ":52@N", 
3495          ":53@N"] 
3496   
3497          # Load the data. 
3498          #self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3499          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
3500   
3501          # Set pipe name, bundle and type. 
3502          pipe_name = 'base pipe' 
3503          pipe_bundle = 'relax_disp' 
3504          pipe_type = 'relax_disp' 
3505   
3506          # Create the data pipe. 
3507          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
3508   
3509          file = data_path + '1_setup_r1rho_GUI.py' 
3510          self.interpreter.script(file=file, dir=None) 
3511   
3512          # The dispersion models. 
3513          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3514   
3515          # The grid search size (the number of increments per dimension). 
3516          GRID_INC = None 
3517   
3518          # The number of Monte Carlo simulations to be used for error analysis for exponential curve fitting of R2eff. 
3519          # When set to minus 1, estimation of the errors will be extracted from the covariance matrix. 
3520          # This is HIGHLY likely to be wrong, but can be used in an initial test fase. 
3521          EXP_MC_NUM = -1 
3522   
3523          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3524          MC_NUM = 3 
3525   
3526          # Model selection technique. 
3527          MODSEL = 'AIC' 
3528   
3529          # Execute the auto-analysis (fast). 
3530          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3531          OPT_FUNC_TOL = 1e-25 
3532          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3533          OPT_MAX_ITERATIONS = 10000000 
3534          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3535   
3536          # Make all spins free 
3537          #for curspin in cluster_ids: 
3538          #    self.interpreter.relax_disp.cluster('free spins', curspin) 
3539          #    # Shut them down 
3540          #    self.interpreter.deselect.spin(spin_id=curspin, boolean='OR', change_all=False) 
3541   
3542          # Make all spins free 
3543          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
3544   
3545          # Select only a subset of spins for global fitting 
3546          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3547          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3548   
3549          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3550          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3551   
3552          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3553          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3554   
3555          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3556              print(spin_id) 
3557   
3558          result_dir_name = self.tmpdir 
3559          r1_fit = True 
3560   
3561          # Run the analysis. 
3562          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=EXP_MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3563   
3564          # Verify the data. 
3565          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3566   
3567   
3568 -    def test_estimate_r2eff_err_methods(self): 
3569          """Test the user function for estimating R2eff and associated errors for exponential curve fitting with different methods. 
3570          This is compared with a run where erros are estimated by 2000 Monte Carlo simulations. 
3571   
3572          This follows Task 7822. 
3573          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3574   
3575          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3576          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3577   
3578          NOTE: The difference in the methods was due to a bug in relax! 
3579          U{bug #22554<https://gna.org/bugs/index.php?22554>}. The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected. 
3580   
3581          This dataset is old, and includes 2000 Monte-Carlo simulations, which is performed wrong. 
3582          """ 
3583   
3584          # Define data path. 
3585          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
3586   
3587          # Create pipe. 
3588          self.interpreter.pipe.create('MC_2000', 'relax_disp') 
3589   
3590          # Read results for 2000 MC simulations. 
3591          self.interpreter.results.read(prev_data_path + sep + 'results') 
3592   
3593          # Start dic. 
3594          my_dic = {} 
3595          param_key_list = [] 
3596   
3597          # Do boot strapping ? 
3598          do_boot = True 
3599          if do_boot: 
3600              min_algor = 'Newton' 
3601              min_options = () 
3602              sim_boot = 200 
3603              scaling_list = [1.0, 1.0] 
3604   
3605          # First check sim values. 
3606          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3607              # Add key to dic. 
3608              my_dic[spin_id] = {} 
3609   
3610              # Loop over sim. 
3611              for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3612                  # Loop over all exp type. 
3613                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3614                      # Generate the param_key. 
3615                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3616                      r2eff_sim_point = r2eff_sim[param_key] 
3617                      i0_sim_point = cur_spin.r2eff_sim[i][param_key] 
3618   
3619                      # Assert point are higher than 0.0. 
3620                      #point_info = "r2eff=%3.2f i0=%3.2f, at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f, at sim index %i." % (r2eff_sim_point, i0_sim_point, frq/1E6, offset, point, i) 
3621                      #print(point_info) 
3622                      self.assert_(r2eff_sim_point > 0.0) 
3623                      self.assert_(i0_sim_point > 0.0) 
3624   
3625          # Get the data. 
3626          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3627              # Generate spin string. 
3628              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3629   
3630              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3631                  # Generate the param_key. 
3632                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3633   
3634                  # Loop over all sim, and collect data. 
3635                  r2eff_sim_l = [] 
3636                  i0_sim_l = [] 
3637                  for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3638                      i0_sim = cur_spin.i0_sim[i] 
3639   
3640                      r2eff_sim_i = r2eff_sim[param_key] 
3641                      r2eff_sim_l.append(r2eff_sim_i) 
3642                      i0_sim_i = i0_sim[param_key] 
3643                      i0_sim_l.append(i0_sim_i) 
3644   
3645                  # Take the standard deviation of all values. 
3646                  r2eff_sim_err = std(asarray(r2eff_sim_l), ddof=1) 
3647                  i0_sim_err = std(asarray(i0_sim_l), ddof=1) 
3648   
3649                  # Append key. 
3650                  param_key_list.append(param_key) 
3651   
3652                  # Add key to dic. 
3653                  my_dic[spin_id][param_key] = {} 
3654   
3655                  # Get the value. 
3656                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
3657                  r2eff_err = getattr(cur_spin, 'r2eff_err')[param_key] 
3658                  i0 = getattr(cur_spin, 'i0')[param_key] 
3659                  i0_err = getattr(cur_spin, 'i0_err')[param_key] 
3660   
3661                  # Save to dic. 
3662                  my_dic[spin_id][param_key]['r2eff'] = r2eff 
3663                  my_dic[spin_id][param_key]['r2eff_err'] = r2eff_err 
3664                  my_dic[spin_id][param_key]['i0'] = i0 
3665                  my_dic[spin_id][param_key]['i0_err'] = i0_err 
3666                  my_dic[spin_id][param_key]['r2eff_err_sim'] = r2eff_sim_err 
3667                  my_dic[spin_id][param_key]['i0_err_sim'] = i0_sim_err 
3668   
3669                  # Assert values are equal 
3670                  self.assertAlmostEqual(r2eff_sim_err, r2eff_err) 
3671                  self.assertAlmostEqual(i0_sim_err, i0_err) 
3672   
3673                  if do_boot: 
3674                      values = [] 
3675                      errors = [] 
3676                      times = [] 
3677                      for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
3678                          values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
3679                          errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
3680                          times.append(time) 
3681   
3682                      # Convert to numpy array. 
3683                      values = asarray(values) 
3684                      errors = asarray(errors) 
3685                      times = asarray(times) 
3686   
3687                      R_m_sim_l = [] 
3688                      I0_m_sim_l = [] 
3689                      for j in range(sim_boot): 
3690                          if j in range(0, 100000, 100): 
3691                              print("Simulation %i"%j) 
3692                          # Start minimisation. 
3693   
3694                          # Produce errors 
3695                          I_err = [] 
3696                          for j, error in enumerate(errors): 
3697                              I_error = gauss(values[j], error) 
3698                              I_err.append(I_error) 
3699                          # Convert to numpy array. 
3700                          I_err = asarray(I_err) 
3701   
3702                          x0 = [r2eff, i0] 
3703                          model = Relax_fit_opt(model='exp', num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3704   
3705                          params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, full_output=True, print_flag=0) 
3706                          R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
3707                          R_m_sim_l.append(R_m_sim_j) 
3708                          I0_m_sim_l.append(I0_m_sim_j) 
3709   
3710                      # Get stats on distribution. 
3711                      sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
3712                      sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
3713                      my_dic[spin_id][param_key]['r2eff_err_boot'] = sigma_R_sim 
3714                      my_dic[spin_id][param_key]['i0_err_boot'] = sigma_I0_sim 
3715   
3716   
3717          # A new data pipe. 
3718          self.interpreter.pipe.copy(pipe_from='MC_2000', pipe_to='r2eff_est') 
3719          self.interpreter.pipe.switch(pipe_name='r2eff_est') 
3720   
3721          # Delete old errors. 
3722          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3723              delattr(cur_spin, 'r2eff_err') 
3724              delattr(cur_spin, 'i0_err') 
3725   
3726          # Set the model. 
3727          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3728   
3729          # Estimate R2eff and errors. 
3730          self.interpreter.relax_disp.r2eff_err_estimate(verbosity=0) 
3731   
3732          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3733              # Generate spin string. 
3734              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3735   
3736              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3737                  # Generate the param_key. 
3738                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3739   
3740                  # Get the value. 
3741                  r2eff_est = getattr(cur_spin, 'r2eff')[param_key] 
3742                  r2eff_err_est = getattr(cur_spin, 'r2eff_err')[param_key] 
3743                  i0_est = getattr(cur_spin, 'i0')[param_key] 
3744                  i0_err_est = getattr(cur_spin, 'i0_err')[param_key] 
3745   
3746                  # Get from dic. 
3747                  r2eff = my_dic[spin_id][param_key]['r2eff'] 
3748                  r2eff_err = my_dic[spin_id][param_key]['r2eff_err'] 
3749                  i0 = my_dic[spin_id][param_key]['i0'] 
3750                  i0_err = my_dic[spin_id][param_key]['i0_err'] 
3751                  r2eff_sim_err = my_dic[spin_id][param_key]['r2eff_err_sim'] 
3752                  i0_sim_err = my_dic[spin_id][param_key]['i0_err_sim'] 
3753   
3754                  if do_boot: 
3755                      r2eff_boot_err = my_dic[spin_id][param_key]['r2eff_err_boot'] 
3756                      i0_boot_err = my_dic[spin_id][param_key]['i0_err_boot'] 
3757                  else: 
3758                      r2eff_boot_err = 0.0 
3759                      i0_boot_err = 0.0 
3760   
3761                  print("%s at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f." % (exp_type, frq/1E6, offset, point) ) 
3762                  print("r2eff=%3.3f/%3.3f r2eff_err=%3.4f/%3.4f/%3.4f/%3.4f" % (r2eff, r2eff_est, r2eff_err, r2eff_err_est, r2eff_sim_err, r2eff_boot_err) ), 
3763                  print("i0=%3.3f/%3.3f i0_err=%3.4f/%3.4f/%3.4f/%3.4f\n" % (i0, i0_est, i0_err, i0_err_est, i0_sim_err, i0_boot_err) ) 
3764   
3765   
3766          # Now do it manually. 
3767          estimate_r2eff(method='scipy.optimize.leastsq') 
3768   
3769          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=False) 
3770          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=True) 
3771   
3772          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=False) 
3773          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=True) 
3774   
3775          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=False) 
3776          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=True) 
3777   
3778          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=False) 
3779          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=True) 
3780   
3781          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=False) 
3782          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=True) 
3783   
3784   
3785   
3786 -    def test_exp_fit(self): 
3787          """Test the relaxation dispersion 'exp_fit' model curve fitting.""" 
3788   
3789          # Execute the script. 
3790          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'exp_fit.py') 
3791   
3792          # The original exponential curve parameters. 
3793          res_data = [ 
3794              [15., 10., 20000., 25000.], 
3795              [12., 11., 50000., 51000.], 
3796              [17., 9., 100000., 96000.] 
3797          ] 
3798   
3799          # List of parameters which do not belong to the model. 
3800          blacklist = ['cpmg_frqs', 'r2', 'rex', 'kex', 'r2a', 'k_AB', 'dw'] 
3801   
3802          # Checks for each residue. 
3803          for i in range(len(res_data)): 
3804              # Printout. 
3805              print("\nResidue number %s." % (i+1)) 
3806   
3807              # Check the fitted parameters. 
3808              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_1000.000'], res_data[i][0], places=2) 
3809              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_2000.000'], res_data[i][1], places=2) 
3810              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_1000.000']/10000, res_data[i][2]/10000, places=3) 
3811              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_2000.000']/10000, res_data[i][3]/10000, places=3) 
3812   
3813              # Check the simulation errors. 
3814              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_1000.000'] < 5.0) 
3815              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_2000.000'] < 5.0) 
3816              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_1000.000']/10000 < 5.0) 
3817              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_2000.000']/10000 < 5.0) 
3818   
3819              # Check that certain parameters are not present. 
3820              for param in blacklist: 
3821                  print("\tChecking for the absence of the '%s' parameter." % param) 
3822                  self.assert_(not hasattr(cdp.mol[0].res[i].spin[0], param)) 
3823   
3824          # Check the clustering information. 
3825          self.assert_(hasattr(cdp, 'clustering')) 
3826          keys = ['free spins', 'cluster'] 
3827          for key in keys: 
3828              self.assert_(key in cdp.clustering) 
3829          self.assert_('test' not in cdp.clustering) 
3830          self.assertEqual(cdp.clustering['free spins'], [':2@N']) 
3831          self.assertEqual(cdp.clustering['cluster'], [':1@N', ':3@N']) 
3832   
3833   
3834 -    def test_finite_value(self): 
3835          """Test return from C code, when parameters are wrong.  This can happen, if minfx takes a wrong step.""" 
3836   
3837          times = array([ 0.7,  1.,  0.8,  0.4,  0.9]) 
3838          I = array([ 476.76174875,  372.43328777,  454.20339981,  656.87936253,  419.16726341]) 
3839          errors = array([  9.48032653,  11.34093541,   9.35149017,  10.84867928,  12.17590736]) 
3840   
3841          scaling_list = [1.0, 1.0] 
3842          model = Relax_fit_opt(model='exp', num_params=2, values=I, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3843   
3844          R = - 500. 
3845          I0 = 1000. 
3846          params = [R, I0] 
3847   
3848          chi2 = model.func(params) 
3849   
3850          print("The chi2 value returned from C-code for R=%3.2f and I0=%3.2f, then chi2=%3.2f"%(R, I0, chi2)) 
3851          self.assertNotEqual(chi2, inf) 
3852   
3853   
3854 -    def test_hansen_catia_input(self): 
3855          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CATIA. 
3856   
3857          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3858          """ 
3859   
3860          # Load the R2eff results file. 
3861          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
3862          self.interpreter.results.read(file_name) 
3863          self.interpreter.deselect.spin(':4') 
3864   
3865          # The spin isotopes. 
3866          self.interpreter.spin.isotope("15N") 
3867   
3868          # Generate the input files. 
3869          self.interpreter.relax_disp.catia_input(dir=ds.tmpdir, force=True) 
3870   
3871          # Check the r2eff set files. 
3872          print("\nChecking the R2eff input set files.") 
3873          files = ['data_set_500.inp', 'data_set_500.inp'] 
3874          for file in files: 
3875              self.assert_(access(ds.tmpdir+sep+file, F_OK)) 
3876          data_set_500 = [ 
3877              "ID=500\n", 
3878              "Sfrq = 500\n", 
3879              "Temperature = 0.0\n", 
3880              "Nucleus = N15\n", 
3881              "Couplednucleus = H1\n", 
3882              "Time_equil = 0.0\n", 
3883              "Pwx_cp = 0.0\n", 
3884              "Taub = 0.0\n", 
3885              "Time_T2 = 0.03\n", 
3886              "Xcar = 0.0\n", 
3887              "Seqfil = CW_CPMG\n", 
3888              "Minerror = (2.%;0.5/s)\n", 
3889              "Basis = (Iph_7)\n", 
3890              "Format = (0;1;2)\n", 
3891              "DataDirectory = /tmp/tmpNjOGNG/input_r2eff\n", 
3892              "Data = (\n", 
3893              " [70N;spin_70_N_500.cpmg];\n", 
3894              " [71N;spin_71_N_500.cpmg];\n", 
3895              ")\n", 
3896          ] 
3897          file = open(ds.tmpdir+sep+files[0]) 
3898          lines = file.readlines() 
3899          file.close() 
3900          for i in range(len(data_set_500)): 
3901              # Skip the data directory, as this is a random file name. 
3902              if i == 14: 
3903                  continue 
3904   
3905              self.assertEqual(data_set_500[i], lines[i]) 
3906   
3907          # Check the r2eff files. 
3908          print("\nChecking the R2eff input files.") 
3909          files = ['spin_70_N_500.cpmg', 'spin_70_N_800.cpmg', 'spin_71_N_500.cpmg', 'spin_71_N_800.cpmg'] 
3910          for file in files: 
3911              self.assert_(access(ds.tmpdir+sep+'input_r2eff'+sep+file, F_OK)) 
3912          spin_70_N_500 = [ 
3913              "#        nu_cpmg(Hz)              R2(1/s)              Esd(R2)\n", 
3914              "  66.666600000000003   16.045540885533605    0.310924686180635\n", 
3915              " 133.333300000000008   14.877924861181727    0.303217270671013\n", 
3916              " 200.000000000000000   14.357820247260586    0.299894424543361\n", 
3917              " 266.666600000000017   12.664494620416516    0.289532060485796\n", 
3918              " 333.333300000000008   12.363204802467891    0.287759631749322\n", 
3919              " 400.000000000000000   11.092532381134513    0.280514035409862\n", 
3920              " 466.666600000000017   10.566090057649893    0.277618625949722\n", 
3921              " 533.333300000000008    9.805806894657803    0.273544382200754\n", 
3922              " 600.000000000000000    9.564300692201730    0.272276309984954\n", 
3923              " 666.666600000000017    9.015633750407980    0.269441511838159\n", 
3924              " 733.333300000000008    8.607764958055581    0.267375134391053\n", 
3925              " 800.000000000000000    8.279997179221338    0.265739551961997\n", 
3926              " 866.666600000000017    8.474535940963516    0.266707642726566\n", 
3927              " 933.333300000000008    8.158972897365194    0.265141210539941\n", 
3928              "1000.000000000000000    7.988630509501972    0.264304105548559\n", 
3929          ] 
3930          file = open(ds.tmpdir+sep+'input_r2eff'+sep+files[0]) 
3931          lines = file.readlines() 
3932          file.close() 
3933          for i in range(len(lines)): 
3934              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
3935          for i in range(len(spin_70_N_500)): 
3936              self.assertEqual(spin_70_N_500[i], lines[i]) 
3937   
3938          # Check the main file. 
3939          print("\nChecking the main CATIA execution file.") 
3940          main_file = [ 
3941              "ReadDataset(data_set_500.inp)\n", 
3942              "ReadDataset(data_set_800.inp)\n", 
3943              "ReadParam_Global(ParamGlobal.inp)\n", 
3944              "ReadParam_Local(ParamSet1.inp)\n", 
3945              "\n", 
3946              "FreeLocalParam(all;Omega;false)\n", 
3947              "FreeLocalParam(all;R1iph_500;false)\n", 
3948              "FreeLocalParam(all;R1iph_800;false)\n", 
3949              "\n", 
3950              "Minimize(print=y;tol=1e-25;maxiter=10000000)\n", 
3951              "\n", 
3952              "PrintParam(output/GlobalParam.fit;global)\n", 
3953              "PrintParam(output/DeltaOmega.fit;DeltaO)\n", 
3954              "PrintData(output/)\n", 
3955              "\n", 
3956              "ChiSq(all;all)\n", 
3957              "exit(0)\n" 
3958          ] 
3959          file = open("%s%sFit.catia" % (ds.tmpdir, sep)) 
3960          lines = file.readlines() 
3961          file.close() 
3962          for i in range(len(main_file)): 
3963              self.assertEqual(main_file[i], lines[i]) 
3964   
3965   
3966 -    def test_hansen_cpmg_data_auto_analysis(self): 
3967          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3968   
3969          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3970          """ 
3971   
3972          # Set the model. 
3973          ds.models = [ 
3974              MODEL_NOREX, 
3975              MODEL_LM63, 
3976              MODEL_CR72, 
3977              MODEL_IT99 
3978          ] 
3979   
3980          # Execute the script. 
3981          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
3982          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
3983   
3984          # The R20 keys. 
3985          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
3986          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
3987   
3988          # The 'No Rex' model checks. 
3989          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
3990          spin70 = return_spin(":70") 
3991          spin71 = return_spin(":71") 
3992          print("\n\nOptimised parameters:\n") 
3993          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
3994          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
3995          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
3996          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
3997          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
3998          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
3999          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
4000          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4001          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4002          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
4003   
4004          # The 'LM63' model checks. 
4005          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
4006          spin70 = return_spin(":70") 
4007          spin71 = return_spin(":71") 
4008          print("\n\nOptimised parameters:\n") 
4009          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4010          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4011          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4012          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4013          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4014          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4015          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
4016          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
4017          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
4018          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
4019          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
4020          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
4021          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
4022          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
4023          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
4024          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
4025   
4026          # The 'CR72' model checks. 
4027          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4028          spin70 = return_spin(":70") 
4029          spin71 = return_spin(":71") 
4030          print("\n\nOptimised parameters:\n") 
4031          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4032          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4033          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4034          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4035          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4036          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4037          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4038          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4039          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4040          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4041          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4042          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4043          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4044          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
4045          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4046          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4047          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4048          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4049          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4050   
4051   
4052 -    def test_hansen_cpmg_data_auto_analysis_numeric(self): 
4053          """Test of the numeric model only dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
4054   
4055          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4056          """ 
4057   
4058          # Set the model and numeric flag. 
4059          ds.models = [ 
4060              MODEL_NOREX, 
4061              MODEL_CR72, 
4062              MODEL_NS_CPMG_2SITE_EXPANDED 
4063          ] 
4064          ds.numeric_only = True 
4065   
4066          # Execute the script. 
4067          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
4068   
4069          # The R20 keys. 
4070          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4071          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4072   
4073          # The 'No Rex' model checks. 
4074          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4075          spin70 = return_spin(":70") 
4076          spin71 = return_spin(":71") 
4077          print("\n\nOptimised parameters:\n") 
4078          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4079          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4080          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4081          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4082          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4083          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4084          self.assertAlmostEqual(spin70.chi2/10000, 8973.84810025761/10000, 3) 
4085          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4086          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4087          self.assertAlmostEqual(spin71.chi2/10000, 3908.00127830003/10000, 3) 
4088   
4089          # The 'CR72' model checks. 
4090          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4091          spin70 = return_spin(":70") 
4092          spin71 = return_spin(":71") 
4093          print("\n\nOptimised parameters:\n") 
4094          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4095          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4096          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4097          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4098          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4099          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4100          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4101          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4102          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4103          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4104          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4105          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4106          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4107          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
4108          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4109          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4110          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4111          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4112          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4113   
4114          # The 'NS CPMG 2-site expanded' model checks. 
4115          self.interpreter.pipe.switch(pipe_name='NS CPMG 2-site expanded - relax_disp') 
4116          spin70 = return_spin(":70") 
4117          spin71 = return_spin(":71") 
4118          print("\n\nOptimised parameters:\n") 
4119          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4120          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4121          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4122          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4123          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4124          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4125          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4126          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95815351460902, 3) 
4127          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39649535771294, 3) 
4128          self.assertAlmostEqual(spin70.pA, 0.989701014493195, 3) 
4129          self.assertAlmostEqual(spin70.dw, 5.67314464776128, 3) 
4130          self.assertAlmostEqual(spin70.kex/10000, 1713.65380495429/10000, 3) 
4131          self.assertAlmostEqual(spin70.chi2, 52.5106880917473, 3) 
4132          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99889337382435, 3) 
4133          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89822887466673, 3) 
4134          self.assertAlmostEqual(spin71.pA, 0.986709050819695, 3) 
4135          self.assertAlmostEqual(spin71.dw, 2.09238266766502, 2) 
4136          self.assertAlmostEqual(spin71.kex/10000, 2438.27019901422/10000, 3) 
4137          self.assertAlmostEqual(spin71.chi2, 15.1644906963987, 3) 
4138   
4139          # The final data pipe checks. 
4140          self.interpreter.pipe.switch(pipe_name='final - relax_disp') 
4141          spin70 = return_spin(":70") 
4142          spin71 = return_spin(":71") 
4143          self.assertEqual(spin70.model, 'NS CPMG 2-site expanded') 
4144          self.assertEqual(spin71.model, 'NS CPMG 2-site expanded') 
4145   
4146   
4147 -    def test_hansen_cpmg_data_auto_analysis_r2eff(self): 
4148          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data (using the R2eff data directly instead of peak intensities). 
4149   
4150          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4151          """ 
4152   
4153          # Set the model. 
4154          ds.models = [ 
4155              MODEL_NOREX, 
4156              MODEL_LM63, 
4157              MODEL_CR72, 
4158              MODEL_IT99 
4159          ] 
4160   
4161          # Execute the script. 
4162          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_r2eff_data.py') 
4163          self.interpreter.state.save('analysis_r2eff', dir=ds.tmpdir, force=True) 
4164   
4165          # The R20 keys. 
4166          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4167          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4168   
4169          # The 'No Rex' model checks. 
4170          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4171          spin70 = return_spin(":70") 
4172          spin71 = return_spin(":71") 
4173          print("\n\nOptimised parameters:\n") 
4174          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4175          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4176          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4177          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4178          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4179          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4180          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
4181          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4182          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4183          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
4184   
4185          # The 'LM63' model checks. 
4186          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
4187          spin70 = return_spin(":70") 
4188          spin71 = return_spin(":71") 
4189          print("\n\nOptimised parameters:\n") 
4190          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4191          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4192          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4193          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4194          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4195          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4196          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
4197          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
4198          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
4199          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
4200          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
4201          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
4202          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
4203          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
4204          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
4205          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
4206   
4207          # The 'CR72' model checks. 
4208          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4209          spin70 = return_spin(":70") 
4210          spin71 = return_spin(":71") 
4211          print("\n\nOptimised parameters:\n") 
4212          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4213          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4214          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4215          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4216          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4217          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4218          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4219          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4220          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4221          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4222          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4223          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4224          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4225          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00317154730225, 3) 
4226          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797713541, 3) 
4227          self.assertAlmostEqual(spin71.pA, 0.985922406429147, 3) 
4228          self.assertAlmostEqual(spin71.dw, 2.00500965887772, 2) 
4229          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579804/10000, 3) 
4230          self.assertAlmostEqual(spin71.chi2, 15.6595374288635, 3) 
4231   
4232   
4233 -    def test_hansen_cpmg_data_missing_auto_analysis(self): 
4234          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data with parts missing. 
4235   
4236          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4237          """ 
4238   
4239          # Set the model. 
4240          ds.models = [ 
4241              MODEL_R2EFF, 
4242              MODEL_NOREX, 
4243              MODEL_CR72, 
4244              MODEL_NS_CPMG_2SITE_EXPANDED 
4245          ] 
4246   
4247          # Execute the script. 
4248          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data_missing.py') 
4249          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
4250   
4251          # The R20 keys. 
4252          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4253          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4254   
4255          # The 'No Rex' model checks. 
4256          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4257          spin4 = return_spin(":4") 
4258          spin70 = return_spin(":70") 
4259          spin71 = return_spin(":71") 
4260          print("\n\nOptimised parameters:\n") 
4261          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4262          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4263          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4264          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4265          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463084515171, 3) 
4266          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63220784651911, 3) 
4267          self.assertAlmostEqual(spin4.chi2, 26.7356700694891, 3) 
4268          self.assertAlmostEqual(spin70.r2[r20_key1], 10.534285641325, 3) 
4269          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112794857068, 3) 
4270          self.assertAlmostEqual(spin70.chi2, 8973.84809774722, 3) 
4271          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83136858890037, 3) 
4272          self.assertAlmostEqual(spin71.chi2, 182.60081909193, 3) 
4273   
4274          # The 'CR72' model checks. 
4275          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4276          spin4 = return_spin(":4") 
4277          spin70 = return_spin(":70") 
4278          spin71 = return_spin(":71") 
4279          print("\n\nOptimised parameters:\n") 
4280          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4281          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4282          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4283          print("%-20s %20.15g %20.15g %20.15g" % ("pA", spin4.pA, spin70.pA, spin71.pA)) 
4284          print("%-20s %20.15g %20.15g %20.15g" % ("dw", spin4.dw, spin70.dw, spin71.dw)) 
4285          print("%-20s %20.15g %20.15g %20.15g" % ("kex", spin4.kex, spin70.kex, spin71.kex)) 
4286          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4287          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463650370664, 2) 
4288          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63221675941434, 3) 
4289          #self.assertAlmostEqual(spin4.pA, 0.818979078699935, 3)    # As dw (and kex) is zero, this parameter is not stable. 
4290          self.assertAlmostEqual(spin4.dw, 0.0, 2) 
4291          self.assertAlmostEqual(spin4.kex/10000, 0.0, 3) 
4292          self.assertAlmostEqual(spin4.chi2/100, 26.7356711142038/100, 3) 
4293          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97268077496405, 3) 
4294          self.assertAlmostEqual(spin70.r2[r20_key2], 9.41028133407727, 3) 
4295          self.assertAlmostEqual(spin70.pA, 0.989856641885939, 3) 
4296          self.assertAlmostEqual(spin70.dw, 5.60889911049405, 3) 
4297          self.assertAlmostEqual(spin70.kex/10000, 1752.62025618632/10000, 3) 
4298          self.assertAlmostEqual(spin70.chi2, 53.8382196964083, 3) 
4299          self.assertAlmostEqual(spin71.r2[r20_key1], 4.98123328466942, 3) 
4300          self.assertAlmostEqual(spin71.pA, 0.996607425484157, 3) 
4301          self.assertAlmostEqual(spin71.dw, 4.34346257383825, 2) 
4302          self.assertAlmostEqual(spin71.kex/10000, 1936.73197158804/10000, 3) 
4303          self.assertAlmostEqual(spin71.chi2, 5.51703791653689, 3) 
4304   
4305   
4306 -    def test_hansen_cpmg_data_to_cr72(self): 
4307          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 dispersion model. 
4308   
4309          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4310          """ 
4311   
4312          # Base data setup. 
4313          self.setup_hansen_cpmg_data(model='CR72') 
4314   
4315          # Alias the spins. 
4316          spin70 = return_spin(":70") 
4317          spin71 = return_spin(":71") 
4318   
4319          # The R20 keys. 
4320          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4321          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4322   
4323          # Set the initial parameter values. 
4324          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4325          spin70.pA = 0.9 
4326          spin70.dw = 6.0 
4327          spin70.kex = 1500.0 
4328          spin71.r2 = {r20_key1: 5, r20_key2: 9.0} 
4329          spin71.pA = 0.9 
4330          spin71.dw = 4.0 
4331          spin71.kex = 1900.0 
4332   
4333          # Low precision optimisation. 
4334          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4335   
4336          # Printout. 
4337          print("\n\nOptimised parameters:\n") 
4338          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4339          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4340          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4341          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4342          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4343          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4344          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4345   
4346          # Checks for residue :70. 
4347          self.assertAlmostEqual(spin70.r2[r20_key1], 6.9724581325007, 4) 
4348          self.assertAlmostEqual(spin70.r2[r20_key2], 9.40968331038162, 2) 
4349          self.assertAlmostEqual(spin70.pA, 0.989856656702431, 4) 
4350          self.assertAlmostEqual(spin70.dw, 5.60885879594746, 3) 
4351          self.assertAlmostEqual(spin70.kex/1000, 1752.91052702273/1000, 3) 
4352          self.assertAlmostEqual(spin70.chi2, 53.8382133597495, 4) 
4353   
4354          # Checks for residue :71. 
4355          self.assertAlmostEqual(spin71.r2[r20_key1], 5.0030740940524, 4) 
4356          self.assertAlmostEqual(spin71.pA, 0.985941082507823, 4) 
4357          self.assertAlmostEqual(spin71.dw, 2.00640384113696, 4) 
4358          self.assertAlmostEqual(spin71.kex/1000, 2480.79614442041/1000, 4) 
4359          self.assertAlmostEqual(spin71.chi2, 15.6595388312451, 4) 
4360   
4361          # Test the conversion to k_AB from kex and pA. 
4362          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4363          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4364   
4365          # Test the conversion to k_BA from kex and pA. 
4366          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4367          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4368   
4369   
4370 -    def test_hansen_cpmg_data_to_cr72_full(self): 
4371          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 full dispersion model. 
4372   
4373          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4374          """ 
4375   
4376          # Base data setup. 
4377          self.setup_hansen_cpmg_data(model='CR72 full') 
4378   
4379          # Alias the spins. 
4380          spin70 = return_spin(":70") 
4381          spin71 = return_spin(":71") 
4382   
4383          # The R20 keys. 
4384          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4385          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4386   
4387          # Set the initial parameter values. 
4388          spin70.r2a = {r20_key1: 7.0, r20_key2: 9.0} 
4389          spin70.r2b = {r20_key1: 7.0, r20_key2: 9.0} 
4390          spin70.pA = 0.9 
4391          spin70.dw = 6.0 
4392          spin70.kex = 1500.0 
4393          spin71.r2a = {r20_key1: 5.0, r20_key2: 9.0} 
4394          spin71.r2b = {r20_key1: 5.0, r20_key2: 9.0} 
4395          spin71.pA = 0.9 
4396          spin71.dw = 4.0 
4397          spin71.kex = 1900.0 
4398   
4399          # Low precision optimisation. 
4400          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4401   
4402          # Printout. 
4403          print("\n\nOptimised parameters:\n") 
4404          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4405          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4406          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4407          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4408          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4409          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4410          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4411          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4412          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4413   
4414          # Checks for residue :70. 
4415          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.87485258365614, 4) 
4416          self.assertAlmostEqual(spin70.r2b[r20_key1], 1.26075839074614, 4) 
4417          self.assertAlmostEqual(spin70.r2a[r20_key2], 8.79580446260797, 4) 
4418          self.assertAlmostEqual(spin70.r2b[r20_key2], 51.188411562843, 4) 
4419          self.assertAlmostEqual(spin70.pA, 0.989384178573802, 4) 
4420          self.assertAlmostEqual(spin70.dw, 5.54738203723682, 4) 
4421          self.assertAlmostEqual(spin70.kex/1000, 1831.4566463179/1000, 4) 
4422          self.assertAlmostEqual(spin70.chi2, 50.450410782403, 4) 
4423   
4424          # Checks for residue :71. 
4425          self.assertAlmostEqual(spin71.r2a[r20_key1], 5.04185695754972, 4) 
4426          self.assertAlmostEqual(spin71.r2b[r20_key1], 1.62857899941921, 4) 
4427          self.assertAlmostEqual(spin71.pA, 0.988832866751676, 4) 
4428          self.assertAlmostEqual(spin71.dw, 2.24905251856265, 4) 
4429          self.assertAlmostEqual(spin71.kex/1000, 2397.64122642946/1000, 4) 
4430          self.assertAlmostEqual(spin71.chi2, 15.8586492923672, 4) 
4431   
4432          # Test the conversion to k_AB from kex and pA. 
4433          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4434          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4435   
4436          # Test the conversion to k_BA from kex and pA. 
4437          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4438          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4439   
4440   
4441 -    def test_hansen_cpmg_data_to_it99(self): 
4442          """Optimisation of Dr. Flemming Hansen's CPMG data to the IT99 dispersion model. 
4443   
4444          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4445          """ 
4446   
4447          # Base data setup. 
4448          self.setup_hansen_cpmg_data(model='IT99') 
4449   
4450          # Alias the spins. 
4451          spin70 = return_spin(":70") 
4452          spin71 = return_spin(":71") 
4453   
4454          # The R20 keys. 
4455          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4456          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4457   
4458          # Set the initial parameter values. 
4459          spin70.r2 = {r20_key1: 8.8, r20_key2: 16.6} 
4460          spin70.dw = 10.0 
4461          spin70.pA = 0.5 
4462          spin70.tex = 1000.09 
4463          spin71.r2 = {r20_key1: 1.0, r20_key2: 1.0} 
4464          spin71.dw = 10.0 
4465          spin71.pA = 0.95 
4466          spin71.tex = 0.1 
4467   
4468          # Low precision optimisation. 
4469          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-10, grad_tol=None, max_iter=10000, constraints=True, scaling=True, verbosity=1) 
4470   
4471          # Printout. 
4472          print("\n\nOptimised parameters:\n") 
4473          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4474          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4475          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4476          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4477          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4478          print("%-20s %20.15g %20.15g" % ("tex", spin70.tex, spin71.tex)) 
4479          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4480   
4481          # Checks for residue :70. 
4482          self.assertAlmostEqual(spin70.r2[r20_key1], 7.24471197811838, 4) 
4483          self.assertAlmostEqual(spin70.r2[r20_key2], 10.0571040704729, 4) 
4484          self.assertAlmostEqual(spin70.dw, 5.2116923222744, 4) 
4485          self.assertAlmostEqual(spin70.pA, 0.990253627907212, 4) 
4486          self.assertAlmostEqual(spin70.tex*1000, 0.000638394793480444*1000, 4) 
4487          self.assertAlmostEqual(spin70.chi2, 93.5135798618747, 4) 
4488   
4489          # Checks for residue :71. 
4490          self.assertAlmostEqual(spin71.r2[r20_key1], 5.05971235970214, 4) 
4491          self.assertAlmostEqual(spin71.r2[r20_key2], 6.96641194493447, 4) 
4492          self.assertAlmostEqual(spin71.dw, 0.435389946897141, 4) 
4493          self.assertAlmostEqual(spin71.pA, 0.500000000213519, 3) 
4494          self.assertAlmostEqual(spin71.tex*1000, 0.000372436400585538*1000, 4) 
4495          self.assertAlmostEqual(spin71.chi2, 23.7895798801404, 4) 
4496   
4497   
4498 -    def test_hansen_cpmg_data_to_lm63(self): 
4499          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4500   
4501          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4502          """ 
4503   
4504          # Base data setup. 
4505          self.setup_hansen_cpmg_data(model='LM63') 
4506   
4507          # Alias the spins. 
4508          spin70 = return_spin(":70") 
4509          spin71 = return_spin(":71") 
4510   
4511          # The R20 keys. 
4512          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4513          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4514   
4515          # Set the initial parameter values. 
4516          spin70.r2 = {r20_key1: 7.0, r20_key2: 7.0} 
4517          spin70.phi_ex = 0.3 
4518          spin70.kex = 5000.0 
4519          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4520          spin71.phi_ex = 0.1 
4521          spin71.kex = 2500.0 
4522   
4523          # Low precision optimisation. 
4524          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4525   
4526          # Printout. 
4527          print("\n\nOptimised parameters:\n") 
4528          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4529          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4530          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4531          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4532          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4533          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4534   
4535          # Checks for residue :70. 
4536          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74362294539099) 
4537          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406797067481, 6) 
4538          self.assertAlmostEqual(spin70.phi_ex, 0.312733013751449) 
4539          self.assertAlmostEqual(spin70.kex/1000, 4723.09897146338/1000, 6) 
4540          self.assertAlmostEqual(spin70.chi2, 363.534044873483) 
4541   
4542          # Checks for residue :71. 
4543          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00776657729728, 5) 
4544          self.assertAlmostEqual(spin71.phi_ex, 0.0553787825650613, 5) 
4545          self.assertAlmostEqual(spin71.kex/1000, 2781.72292994154/1000, 5) 
4546          self.assertAlmostEqual(spin71.chi2, 17.0776399916287, 5) 
4547   
4548   
4549 -    def test_hansen_cpmg_data_to_lm63_3site(self): 
4550          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4551   
4552          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4553          """ 
4554   
4555          # Base data setup. 
4556          self.setup_hansen_cpmg_data(model='LM63 3-site') 
4557   
4558          # Alias the spins. 
4559          spin70 = return_spin(":70") 
4560          spin71 = return_spin(":71") 
4561   
4562          # The R20 keys. 
4563          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4564          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4565   
4566          ## Set the initial parameter values. 
4567          spin70.r2 = {r20_key1: 7.570370921220954, r20_key2: 8.694446951909107} 
4568          spin70.phi_ex_B = 0.14872003058250227 
4569          spin70.phi_ex_C = 0.1319419923472704 
4570          spin70.kB = 4103.672910444741 
4571          spin70.kC = 7029.001690726248 
4572          spin71.r2 = {r20_key1: 5.1347793381636, r20_key2: 7.156573986051575} 
4573          spin71.phi_ex_B = 0.04013553485505605 
4574          spin71.phi_ex_C = 0.020050748406928887 
4575          spin71.kB = 4045.3007136121364 
4576          spin71.kC = 3586.38798270774 
4577   
4578          #self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
4579          #self.interpreter.minimise.grid_search(lower=None, upper=None, inc=41, constraints=True, verbosity=1) 
4580   
4581          # Low precision optimisation. 
4582          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4583   
4584          # Printout. 
4585          print("\n\nOptimised parameters:\n") 
4586          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4587          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4588          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4589          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin70.phi_ex_B, spin71.phi_ex_B)) 
4590          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin70.phi_ex_C, spin71.phi_ex_C)) 
4591          print("%-20s %20.15g %20.15g" % ("kB", spin70.kB, spin71.kB)) 
4592          print("%-20s %20.15g %20.15g" % ("kC", spin70.kC, spin71.kC)) 
4593          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4594   
4595          # Checks for residue :70. 
4596          self.assertAlmostEqual(spin70.r2[r20_key1], 6.7436230253685, 5) 
4597          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406813008828, 6) 
4598          self.assertAlmostEqual(spin70.phi_ex_B, 0.206304023079778, 5) 
4599          self.assertAlmostEqual(spin70.phi_ex_C, 0.106428983339627, 5) 
4600          self.assertAlmostEqual(spin70.kB/1000, 4723.09897652589/1000, 6) 
4601          self.assertAlmostEqual(spin70.kC/1000, 4723.09876196409/1000, 6) 
4602          self.assertAlmostEqual(spin70.chi2, 363.534044873483, 5) 
4603   
4604          # Checks for residue :71. 
4605          self.assertAlmostEqual(spin71.r2[r20_key1], 4.96612095596752, 5) 
4606          self.assertAlmostEqual(spin71.phi_ex_B, 0.00398262266512895, 5) 
4607          self.assertAlmostEqual(spin71.phi_ex_C, 0.0555791581291262, 5) 
4608          self.assertAlmostEqual(spin71.kB/1000, 1323.33195689832/1000, 5) 
4609          self.assertAlmostEqual(spin71.kC/1000, 3149.58971568059/1000, 5) 
4610          self.assertAlmostEqual(spin71.chi2, 16.2620934464368) 
4611   
4612   
4613 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D(self): 
4614          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D' dispersion model. 
4615   
4616          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4617          """ 
4618   
4619          # Base data setup. 
4620          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D') 
4621   
4622          # Alias the spins. 
4623          spin70 = return_spin(":70") 
4624          spin71 = return_spin(":71") 
4625   
4626          # The R20 keys. 
4627          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4628          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4629   
4630          # Set the initial parameter values. 
4631          spin70.r2 = {r20_key1: 6.994165925, r20_key2: 9.428129427} 
4632          spin70.pA = 0.9897754407 
4633          spin70.dw = 5.642418428 
4634          spin70.kex = 1743.666375 
4635          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4636          spin71.pA = 0.9968032899 
4637          spin71.dw = 4.577891393 
4638          spin71.kex = 1830.044597 
4639   
4640          # Low precision optimisation. 
4641          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4642   
4643          # Printout. 
4644          print("\n\nOptimised parameters:\n") 
4645          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4646          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4647          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4648          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4649          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4650          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4651          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4652   
4653          # Checks for residue :70. 
4654          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95797760459016, 4) 
4655          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39628959312699, 4) 
4656          self.assertAlmostEqual(spin70.pA, 0.989700985380975, 4) 
4657          self.assertAlmostEqual(spin70.dw, 5.6733714171086, 4) 
4658          self.assertAlmostEqual(spin70.kex/1000, 1713.63101361545/1000, 4) 
4659          self.assertAlmostEqual(spin70.chi2, 52.5106928523775, 4) 
4660   
4661          # Checks for residue :71. 
4662          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99893565849977, 4) 
4663          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89825625944034, 4) 
4664          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 4) 
4665          self.assertAlmostEqual(spin71.dw, 2.09292495350993, 4) 
4666          self.assertAlmostEqual(spin71.kex/1000, 2438.04423541463/1000, 4) 
4667          self.assertAlmostEqual(spin71.chi2, 15.164490242352, 4) 
4668   
4669          # Test the conversion to k_AB from kex and pA. 
4670          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4671          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4672   
4673          # Test the conversion to k_BA from kex and pA. 
4674          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4675          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4676   
4677   
4678 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D_full(self): 
4679          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D full' dispersion model. 
4680   
4681          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4682          """ 
4683   
4684          # Base data setup. 
4685          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D full') 
4686   
4687          # Alias the spins. 
4688          spin70 = return_spin(":70") 
4689          spin71 = return_spin(":71") 
4690   
4691          # The R20 keys. 
4692          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4693          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4694   
4695          # Set the initial parameter values. 
4696          spin70.r2a = {r20_key1: 6.644753428, r20_key2: 7.891776687} 
4697          spin70.r2b = {r20_key1: 7.163478485, r20_key2: 138.5170395} 
4698          spin70.pA = 0.9884781357 
4699          spin70.dw = 5.456507396 
4700          spin70.kex = 1906.521189 
4701          spin71.r2a = {r20_key1: 4.99893524108981, r20_key2: 100.0} 
4702          spin71.r2b = {r20_key1: 8.27456243639973, r20_key2: 100.0} 
4703          spin71.pA = 0.986709616684097 
4704          spin71.dw = 2.09245158280905 
4705          spin71.kex = 2438.2766211401 
4706   
4707          # Low precision optimisation. 
4708          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4709   
4710          # Printout. 
4711          print("\n\nOptimised parameters:\n") 
4712          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4713          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4714          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4715          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4716          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4717          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4718          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4719          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4720          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4721   
4722          # Checks for residue :70. 
4723          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.61176004043484, 4) 
4724          self.assertAlmostEqual(spin70.r2b[r20_key1], 7.4869316381241, 4) 
4725          self.assertAlmostEqual(spin70.r2a[r20_key2], 7.78200386067591, 4) 
4726          self.assertAlmostEqual(spin70.r2b[r20_key2], 141.703593742468, 4) 
4727          self.assertAlmostEqual(spin70.pA, 0.988404987055969, 4) 
4728          self.assertAlmostEqual(spin70.dw, 5.4497360203213, 4) 
4729          self.assertAlmostEqual(spin70.kex/1000, 1934.09304607082/1000, 4) 
4730          self.assertAlmostEqual(spin70.chi2, 44.6793752187925, 4) 
4731   
4732          # Checks for residue :71. 
4733          self.assertAlmostEqual(spin71.r2a[r20_key1], 4.6013095731966, 4) 
4734          self.assertAlmostEqual(spin71.r2b[r20_key1], 13.3245678276332, 4) 
4735          self.assertAlmostEqual(spin71.r2a[r20_key2], 2.08243621257779, 4) 
4736          self.assertAlmostEqual(spin71.r2b[r20_key2], 153.355765094575, 4) 
4737          self.assertAlmostEqual(spin71.pA, 0.9665748685124, 4) 
4738          self.assertAlmostEqual(spin71.dw, 1.41898001408953, 4) 
4739          self.assertAlmostEqual(spin71.kex/1000, 2580.65795560688/1000, 4) 
4740          self.assertAlmostEqual(spin71.chi2, 13.4937006732165, 4) 
4741   
4742          # Test the conversion to k_AB from kex and pA. 
4743          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4744          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4745   
4746          # Test the conversion to k_BA from kex and pA. 
4747          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4748          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4749   
4750   
4751 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_expanded(self): 
4752          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site expanded' dispersion model. 
4753   
4754          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4755          """ 
4756   
4757          # Base data setup. 
4758          self.setup_hansen_cpmg_data(model='NS CPMG 2-site expanded') 
4759   
4760          # Alias the spins. 
4761          spin70 = return_spin(":70") 
4762          spin71 = return_spin(":71") 
4763   
4764          # The R20 keys. 
4765          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4766          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4767   
4768          # Set the initial parameter values. 
4769          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4770          spin70.pA = 0.9 
4771          spin70.dw = 6.0 
4772          spin70.kex = 1500.0 
4773          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4774          spin71.pA = 0.9 
4775          spin71.dw = 4.0 
4776          spin71.kex = 1900.0 
4777   
4778          # Low precision optimisation. 
4779          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4780   
4781          # Printout. 
4782          print("\n\nOptimised parameters:\n") 
4783          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4784          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4785          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4786          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4787          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4788          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4789          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4790   
4791          # Checks for residue :70. 
4792          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95813330991529, 4) 
4793          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39663480561524, 4) 
4794          self.assertAlmostEqual(spin70.pA, 0.989700843879574, 4) 
4795          self.assertAlmostEqual(spin70.dw, 5.67315878825691, 4) 
4796          self.assertAlmostEqual(spin70.kex/1000, 1713.56110716632/1000, 4) 
4797          self.assertAlmostEqual(spin70.chi2, 52.5106879242812, 4) 
4798   
4799          # Checks for residue :71. 
4800          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99881666793312, 4) 
4801          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89817482453042, 4) 
4802          self.assertAlmostEqual(spin71.pA, 0.986712911453639, 4) 
4803          self.assertAlmostEqual(spin71.dw, 2.09273069372236, 4) 
4804          self.assertAlmostEqual(spin71.kex/1000, 2438.20525930405/1000, 4) 
4805          self.assertAlmostEqual(spin71.chi2, 15.1644913030633, 4) 
4806   
4807          # Test the conversion to k_AB from kex and pA. 
4808          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4809          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4810   
4811          # Test the conversion to k_BA from kex and pA. 
4812          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4813          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4814   
4815   
4816 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star(self): 
4817          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star' dispersion model. 
4818   
4819          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4820          """ 
4821   
4822          # Base data setup. 
4823          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star') 
4824   
4825          # Alias the spins. 
4826          spin70 = return_spin(":70") 
4827          spin71 = return_spin(":71") 
4828   
4829          # The R20 keys. 
4830          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4831          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4832   
4833          # Set the initial parameter values. 
4834          spin70.r2 = {r20_key1: 6.996327746, r20_key2: 9.452051268} 
4835          spin70.pA = 0.9897519798 
4836          spin70.dw = 5.644862195 
4837          spin70.kex = 1723.820567 
4838          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4839          spin71.pA = 0.9968032899 
4840          spin71.dw = 4.577891393 
4841          spin71.kex = 1830.044597 
4842   
4843          # Low precision optimisation. 
4844          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4845   
4846          # Printout. 
4847          print("\n\nOptimised parameters:\n") 
4848          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4849          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4850          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4851          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4852          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4853          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4854          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4855   
4856          # Checks for residue :70. 
4857          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95543947938561, 1) 
4858          self.assertAlmostEqual(spin70.r2[r20_key2], 9.38991914134929, 1) 
4859          self.assertAlmostEqual(spin70.pA, 0.989702750971153, 3) 
4860          self.assertAlmostEqual(spin70.dw, 5.67527122494516, 1) 
4861          self.assertAlmostEqual(spin70.kex/1000, 1715.72032391817/1000, 1) 
4862          self.assertAlmostEqual(spin70.chi2, 52.5011991483842, 1) 
4863   
4864          # Checks for residue :71. 
4865          self.assertAlmostEqual(spin71.r2[r20_key1], 4.992594256544, 1) 
4866          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 2) 
4867          self.assertAlmostEqual(spin71.dw/100, 2.09292495350993/100, 2) 
4868          self.assertAlmostEqual(spin71.kex/100000, 2438.04423541463/100000, 2) 
4869          self.assertAlmostEqual(spin71.chi2/100, 15.1644902423334/100, 1) 
4870   
4871          # Test the conversion to k_AB from kex and pA. 
4872          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4873          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4874   
4875          # Test the conversion to k_BA from kex and pA. 
4876          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4877          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4878   
4879   
4880 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star_full(self): 
4881          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star full' dispersion model. 
4882   
4883          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4884          """ 
4885   
4886          # Base data setup. 
4887          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star full') 
4888   
4889          # Alias the spins. 
4890          spin70 = return_spin(":70") 
4891          spin71 = return_spin(":71") 
4892   
4893          # The R20 keys. 
4894          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4895          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4896   
4897          # Set the initial parameter values. 
4898          spin70.r2a = {r20_key1: 6.44836878645126, r20_key2: 7.00382877393494} 
4899          spin70.r2b = {r20_key1: 12.2083127421994, r20_key2: 199.862962628402} 
4900          spin70.pA = 0.987648082613451 
4901          spin70.dw = 5.30679853807572 
4902          spin70.kex = 2033.25380420666 
4903          spin71.r2a = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4904          spin71.r2b = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4905          spin71.pA = 0.992258541625787 
4906          spin71.dw = 2.75140650899058 
4907          spin71.kex = 2106.60885247431 
4908   
4909          # Low precision optimisation. 
4910          self.interpreter.minimise.calculate() 
4911   
4912          # Checks for residue :70. 
4913          self.assertAlmostEqual(spin70.chi2/10, 45.773987568491123/10, 2) 
4914          self.assertAlmostEqual(spin71.chi2/10, 17.329385665659192/10, 2) 
4915   
4916   
4917 -    def test_hansen_cpmgfit_input(self): 
4918          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CPMGFit. 
4919   
4920          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4921          """ 
4922   
4923          # Load the R2eff results file. 
4924          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
4925          self.interpreter.results.read(file_name) 
4926          self.interpreter.deselect.spin(':4') 
4927   
4928          # Set up the model. 
4929          self.interpreter.relax_disp.select_model('LM63') 
4930   
4931          # Generate the input files. 
4932          self.interpreter.relax_disp.cpmgfit_input(force=True, dir=ds.tmpdir) 
4933   
4934          # What the files should contain. 
4935          batch_file = ['#! /bin/sh\n', '\n', 'cpmgfit -grid -xmgr -f spin_70_N.in | tee spin_70_N.out\n', 'cpmgfit -grid -xmgr -f spin_71_N.in | tee spin_71_N.out\n'] 
4936          spin1 = [ 
4937              "title :70@N\n", 
4938              "fields 2 11.7432964915 18.7892743865\n", 
4939              "function CPMG\n", 
4940              "R2 1 10 20\n", 
4941              "Rex 0 100.0 100\n", 
4942              "Tau 0 10.0 100\n", 
4943              "xmgr\n", 
4944              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4945              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4946              "@ xaxis ticklabel format decimal\n", 
4947              "@ yaxis ticklabel format decimal\n", 
4948              "@ xaxis ticklabel char size 0.8\n", 
4949              "@ yaxis ticklabel char size 0.8\n", 
4950              "@ world xmin 0.0\n", 
4951              "data\n", 
4952              "0.133333             16.045541            0.310925             11.743296           \n", 
4953              "0.266667             14.877925            0.303217             11.743296           \n", 
4954              "0.400000             14.357820            0.299894             11.743296           \n", 
4955              "0.533333             12.664495            0.289532             11.743296           \n", 
4956              "0.666667             12.363205            0.287760             11.743296           \n", 
4957              "0.800000             11.092532            0.280514             11.743296           \n", 
4958              "0.933333             10.566090            0.277619             11.743296           \n", 
4959              "1.066667             9.805807             0.273544             11.743296           \n", 
4960              "1.200000             9.564301             0.272276             11.743296           \n", 
4961              "1.333333             9.015634             0.269442             11.743296           \n", 
4962              "1.466667             8.607765             0.267375             11.743296           \n", 
4963              "1.600000             8.279997             0.265740             11.743296           \n", 
4964              "1.733333             8.474536             0.266708             11.743296           \n", 
4965              "1.866667             8.158973             0.265141             11.743296           \n", 
4966              "2.000000             7.988631             0.264304             11.743296           \n", 
4967              "0.133333             22.224914            0.166231             18.789274           \n", 
4968              "0.266667             21.230874            0.162377             18.789274           \n", 
4969              "0.400000             20.603704            0.160017             18.789274           \n", 
4970              "0.533333             20.327797            0.158996             18.789274           \n", 
4971              "0.666667             18.855377            0.153719             18.789274           \n", 
4972              "0.800000             18.537531            0.152617             18.789274           \n", 
4973              "0.933333             17.508069            0.149138             18.789274           \n", 
4974              "1.066667             16.035604            0.144391             18.789274           \n", 
4975              "1.200000             15.168192            0.141717             18.789274           \n", 
4976              "1.333333             14.431802            0.139516             18.789274           \n", 
4977              "1.466667             14.034137            0.138354             18.789274           \n", 
4978              "1.600000             12.920148            0.135192             18.789274           \n", 
4979              "1.733333             12.653673            0.134456             18.789274           \n", 
4980              "1.866667             12.610864            0.134338             18.789274           \n", 
4981              "2.000000             11.969303            0.132601             18.789274           \n" 
4982          ] 
4983          spin2 = [ 
4984              "title :71@N\n", 
4985              "fields 2 11.7432964915 18.7892743865\n", 
4986              "function CPMG\n", 
4987              "R2 1 10 20\n", 
4988              "Rex 0 100.0 100\n", 
4989              "Tau 0 10.0 100\n", 
4990              "xmgr\n", 
4991              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4992              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4993              "@ xaxis ticklabel format decimal\n", 
4994              "@ yaxis ticklabel format decimal\n", 
4995              "@ xaxis ticklabel char size 0.8\n", 
4996              "@ yaxis ticklabel char size 0.8\n", 
4997              "@ world xmin 0.0\n", 
4998              "data\n", 
4999              "0.133333             7.044342             0.170035             11.743296           \n", 
5000              "0.266667             6.781033             0.169228             11.743296           \n", 
5001              "0.400000             6.467623             0.168279             11.743296           \n", 
5002              "0.533333             6.333340             0.167876             11.743296           \n", 
5003              "0.666667             6.323238             0.167846             11.743296           \n", 
5004              "0.800000             6.005245             0.166902             11.743296           \n", 
5005              "0.933333             5.767052             0.166203             11.743296           \n", 
5006              "1.066667             5.476968             0.165361             11.743296           \n", 
5007              "1.200000             5.469949             0.165341             11.743296           \n", 
5008              "1.333333             5.295113             0.164838             11.743296           \n", 
5009              "1.466667             5.435648             0.165242             11.743296           \n", 
5010              "1.600000             5.410400             0.165169             11.743296           \n", 
5011              "1.733333             5.437554             0.165247             11.743296           \n", 
5012              "1.866667             5.176844             0.164501             11.743296           \n", 
5013              "2.000000             5.227232             0.164644             11.743296           \n", 
5014              "0.133333             11.530903            0.081928             18.789274           \n", 
5015              "0.266667             10.983094            0.081041             18.789274           \n", 
5016              "0.400000             10.512403            0.080294             18.789274           \n", 
5017              "0.533333             9.984805             0.079473             18.789274           \n", 
5018              "0.666667             9.573163             0.078845             18.789274           \n", 
5019              "0.800000             9.178810             0.078253             18.789274           \n", 
5020              "0.933333             8.935719             0.077893             18.789274           \n", 
5021              "1.066667             8.610147             0.077416             18.789274           \n", 
5022              "1.200000             8.353778             0.077045             18.789274           \n", 
5023              "1.333333             8.173729             0.076787             18.789274           \n", 
5024              "1.466667             8.091607             0.076670             18.789274           \n", 
5025              "1.600000             7.706420             0.076126             18.789274           \n", 
5026              "1.733333             7.709125             0.076129             18.789274           \n", 
5027              "1.866667             7.610856             0.075992             18.789274           \n", 
5028              "2.000000             7.552584             0.075911             18.789274           \n", 
5029          ] 
5030   
5031          # Check the batch file. 
5032          print("\nChecking the batch file.") 
5033          file = open("%s%sbatch_run.sh" % (ds.tmpdir, sep)) 
5034          lines = file.readlines() 
5035          file.close() 
5036          for i in range(len(lines)): 
5037              self.assertEqual(batch_file[i], lines[i]) 
5038   
5039          # Check spin :70@N. 
5040          print("\nChecking the spin :70@N input file.") 
5041          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_70_N')) 
5042          lines = file.readlines() 
5043          file.close() 
5044          for i in range(len(spin1)): 
5045              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
5046          for i in range(len(lines)): 
5047              self.assertEqual(spin1[i], lines[i]) 
5048   
5049          # Check spin :71@N. 
5050          print("\nChecking the spin :71@N input file.") 
5051          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_71_N')) 
5052          lines = file.readlines() 
5053          file.close() 
5054          for i in range(len(lines)): 
5055              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
5056          for i in range(len(spin2)): 
5057              self.assertEqual(spin2[i], lines[i]) 
5058   
5059   
5060 -    def test_korzhnev_2005_15n_dq_data(self): 
5061          """Optimisation of the Korzhnev et al., 2005 15N DQ CPMG data using the 'NS MMQ 2-site' model. 
5062   
5063          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5064   
5065          Here only the 15N DQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5066   
5067              - r2 = {'500': 9.487269007171426, '600': 11.718267257562591, '800': 13.624551743116887}, 
5068              - pA = 0.965402506690231, 
5069              - dw = 0.805197170133360, 
5070              - dwH = -0.595536627771890, 
5071              - kex = 569.003663067619868, 
5072              - chi2 = 9.297671357952812. 
5073          """ 
5074   
5075          # Base data setup. 
5076          self.setup_korzhnev_2005_data(data_list=['DQ']) 
5077   
5078          # Alias the spin. 
5079          spin = return_spin(":9@N") 
5080   
5081          # The R20 keys. 
5082          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5083          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5084          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5085   
5086          # Set the initial parameter values. 
5087          spin.r2 = {r20_key1: 9.48527908326952, r20_key2: 11.7135951595536, r20_key3: 13.6153887849344} 
5088          spin.pA = 0.965638501551899 
5089          spin.dw = 2.8537583461577 
5090          spin.dwH = -0.387633062766635 
5091          spin.kex = 573.704033851592 
5092   
5093          # Low precision optimisation. 
5094          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5095   
5096          # Monte Carlo simulations. 
5097          self.interpreter.monte_carlo.setup(number=3) 
5098          self.interpreter.monte_carlo.create_data(method='back_calc') 
5099          self.interpreter.monte_carlo.initial_values() 
5100          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5101          self.interpreter.monte_carlo.error_analysis() 
5102   
5103          # Plot the dispersion curves. 
5104          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5105   
5106          # Save the results. 
5107          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5108   
5109          # Printout. 
5110          print("\n\nOptimised parameters:\n") 
5111          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5112          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5113          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5114          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5115          print("%-20s %20.15g" % ("pA", spin.pA)) 
5116          print("%-20s %20.15g" % ("dw", spin.dw)) 
5117          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5118          print("%-20s %20.15g" % ("kex", spin.kex)) 
5119          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5120   
5121          # Checks for residue :9. 
5122          self.assertAlmostEqual(spin.r2[r20_key1], 9.4870656457415, 2) 
5123          self.assertAlmostEqual(spin.r2[r20_key2], 11.7183291788929, 2) 
5124          self.assertAlmostEqual(spin.r2[r20_key3], 13.6241729933153, 2) 
5125          self.assertAlmostEqual(spin.pA, 0.965405468217295, 4) 
5126          self.assertAlmostEqual(spin.dw, 2.76835528427355, 1) 
5127          self.assertAlmostEqual(spin.dwH, -0.396489341086363, 2) 
5128          self.assertAlmostEqual(spin.kex/1000, 569.06937047601/1000, 3) 
5129          self.assertAlmostEqual(spin.chi2, 9.29767487125257, 2) 
5130   
5131   
5132 -    def test_korzhnev_2005_15n_mq_data(self): 
5133          """Optimisation of the Korzhnev et al., 2005 15N MQ CPMG data using the 'NS MMQ 2-site' model. 
5134   
5135          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5136   
5137          Here only the 15N MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5138   
5139              - r2 = {'500': 5.993083514798655, '600': 6.622184438384841, '800': 8.640765919352019}, 
5140              - pA = 0.930027999814003, 
5141              - dw = 4.338620619954370, 
5142              - dwH = -0.274250775560818, 
5143              - kex = 344.613362916544475, 
5144              - chi2 = 10.367733168217050. 
5145          """ 
5146   
5147          # Base data setup. 
5148          self.setup_korzhnev_2005_data(data_list=['MQ']) 
5149   
5150          # Alias the spin. 
5151          spin = return_spin(":9@N") 
5152   
5153          # The R20 keys. 
5154          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5155          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5156          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5157   
5158          # Set the initial parameter values. 
5159          spin.r2 = {r20_key1: 6.02016436619016, r20_key2: 6.65421500772308, r20_key3: 8.6729591487622} 
5160          spin.pA = 0.930083249288083 
5161          spin.dw = 4.33890689462363 
5162          spin.dwH = -0.274316585638047 
5163          spin.kex = 344.329651956132 
5164   
5165          # Low precision optimisation. 
5166          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5167   
5168          # Monte Carlo simulations. 
5169          self.interpreter.monte_carlo.setup(number=3) 
5170          self.interpreter.monte_carlo.create_data(method='back_calc') 
5171          self.interpreter.monte_carlo.initial_values() 
5172          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5173          self.interpreter.monte_carlo.error_analysis() 
5174   
5175          # Plot the dispersion curves. 
5176          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5177   
5178          # Save the results. 
5179          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5180   
5181          # Printout. 
5182          print("\n\nOptimised parameters:\n") 
5183          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5184          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5185          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5186          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5187          print("%-20s %20.15g" % ("pA", spin.pA)) 
5188          print("%-20s %20.15g" % ("dw", spin.dw)) 
5189          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5190          print("%-20s %20.15g" % ("kex", spin.kex)) 
5191          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5192   
5193          # Checks for residue :9. 
5194          self.assertAlmostEqual(spin.r2[r20_key1], 5.99503641023038, 1) 
5195          self.assertAlmostEqual(spin.r2[r20_key2], 6.62432897608527, 1) 
5196          self.assertAlmostEqual(spin.r2[r20_key3], 8.64278915809492, 1) 
5197          self.assertAlmostEqual(spin.pA, 0.930036474040713, 3) 
5198          self.assertAlmostEqual(spin.dw, 4.33848403058432, 2) 
5199          self.assertAlmostEqual(spin.dwH, -0.274246558825267, 3) 
5200          self.assertAlmostEqual(spin.kex/1000, 344.626563267384/1000, 3) 
5201          self.assertAlmostEqual(spin.chi2, 10.3677362372789, 2) 
5202   
5203   
5204 -    def test_korzhnev_2005_15n_sq_data(self): 
5205          """Optimisation of the Korzhnev et al., 2005 15N SQ CPMG data using the 'NS MMQ 2-site' model. 
5206   
5207          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5208   
5209          Here only the 15N SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5210   
5211              - r2 = {'500': 8.335037972570017, '600': 8.761366016417508, '800': 10.225001019091822}, 
5212              - pA = 0.950003458294991, 
5213              - dw = 4.358402855315123, 
5214              - kex = 429.906473361926999, 
5215              - chi2 = 17.393331915567252. 
5216          """ 
5217   
5218          # Base data setup. 
5219          self.setup_korzhnev_2005_data(data_list=['SQ']) 
5220   
5221          # Alias the spin. 
5222          spin = return_spin(":9@N") 
5223   
5224          # The R20 keys. 
5225          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5226          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5227          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5228   
5229          # Set the initial parameter values. 
5230          spin.r2 = {r20_key1: 8.334232330326190, r20_key2: 8.756773997879968, r20_key3: 10.219320492033058} 
5231          spin.pA = 0.950310172115387 
5232          spin.dw = 4.356737157889636 
5233          spin.kex = 433.176323890829849 
5234   
5235          # Low precision optimisation. 
5236          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5237   
5238          # Monte Carlo simulations. 
5239          self.interpreter.monte_carlo.setup(number=3) 
5240          self.interpreter.monte_carlo.create_data(method='back_calc') 
5241          self.interpreter.monte_carlo.initial_values() 
5242          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5243          self.interpreter.monte_carlo.error_analysis() 
5244   
5245          # Plot the dispersion curves. 
5246          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5247   
5248          # Save the results. 
5249          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5250   
5251          # Printout. 
5252          print("\n\nOptimised parameters:\n") 
5253          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5254          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5255          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5256          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5257          print("%-20s %20.15g" % ("pA", spin.pA)) 
5258          print("%-20s %20.15g" % ("dw", spin.dw)) 
5259          print("%-20s %20.15g" % ("kex", spin.kex)) 
5260          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5261   
5262          # Checks for residue :9. 
5263          self.assertAlmostEqual(spin.r2[r20_key1], 8.33499994313902, 2) 
5264          self.assertAlmostEqual(spin.r2[r20_key2], 8.76118738798082, 2) 
5265          self.assertAlmostEqual(spin.r2[r20_key3], 10.2250821829928, 1) 
5266          self.assertAlmostEqual(spin.pA, 0.950000281516303, 3) 
5267          self.assertAlmostEqual(spin.dw, 4.35845318983581, 2) 
5268          self.assertAlmostEqual(spin.kex/1000, 429.874510184149/1000, 2) 
5269          self.assertAlmostEqual(spin.chi2, 17.3933357984425, 1) 
5270   
5271   
5272 -    def test_korzhnev_2005_15n_zq_data(self): 
5273          """Optimisation of the Korzhnev et al., 2005 15N ZQ CPMG data using the 'NS MMQ 2-site' model. 
5274   
5275          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5276   
5277          Here only the 15N ZQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5278   
5279              - r2 = {'500': 5.909812628572937, '600': 6.663690132557320, '800': 6.787171647689906}, 
5280              - pA = 0.942452612380140, 
5281              - dw = 0.858972784230892, 
5282              - dwH = 0.087155962730608, 
5283              - kex = 373.219151384798920, 
5284              - chi2 = 23.863208106025152. 
5285          """ 
5286   
5287          # Base data setup. 
5288          self.setup_korzhnev_2005_data(data_list=['ZQ']) 
5289   
5290          # Alias the spin. 
5291          spin = return_spin(":9@N") 
5292   
5293          # The R20 keys. 
5294          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5295          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5296          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5297   
5298          # Set the initial parameter values. 
5299          spin.r2 = {r20_key1: 5.91033272691614, r20_key2: 6.66368695342258, r20_key3: 6.78922219135537} 
5300          spin.pA = 0.942457332074014 
5301          spin.dw = 0.850592422908884 
5302          spin.dwH = 0.0881272284455416 
5303          spin.kex = 372.745483351305 
5304   
5305          # Low precision optimisation. 
5306          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5307   
5308          # Monte Carlo simulations. 
5309          self.interpreter.monte_carlo.setup(number=3) 
5310          self.interpreter.monte_carlo.create_data(method='back_calc') 
5311          self.interpreter.monte_carlo.initial_values() 
5312          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5313          self.interpreter.monte_carlo.error_analysis() 
5314   
5315          # Plot the dispersion curves. 
5316          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5317   
5318          # Save the results. 
5319          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5320   
5321          # Printout. 
5322          print("\n\nOptimised parameters:\n") 
5323          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5324          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5325          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5326          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5327          print("%-20s %20.15g" % ("pA", spin.pA)) 
5328          print("%-20s %20.15g" % ("dw", spin.dw)) 
5329          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5330          print("%-20s %20.15g" % ("kex", spin.kex)) 
5331          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5332   
5333          # Checks for residue :9. 
5334          self.assertAlmostEqual(spin.r2[r20_key1], 5.9098385837035, 2) 
5335          self.assertAlmostEqual(spin.r2[r20_key2], 6.66377885876553, 2) 
5336          self.assertAlmostEqual(spin.r2[r20_key3], 6.78717432941353, 2) 
5337          self.assertAlmostEqual(spin.pA, 0.942457141344462, 4) 
5338          self.assertAlmostEqual(spin.dw, 0.84442055695814, 1) 
5339          self.assertAlmostEqual(spin.dwH, 0.0886367674566058, 2) 
5340          self.assertAlmostEqual(spin.kex/1000, 373.243053643367/1000, 3) 
5341          self.assertAlmostEqual(spin.chi2, 23.863211604121, 1) 
5342   
5343   
5344 -    def test_korzhnev_2005_1h_mq_data(self): 
5345          """Optimisation of the Korzhnev et al., 2005 1H MQ CPMG data using the 'NS MMQ 2-site' model. 
5346   
5347          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5348   
5349          Here only the 1H MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5350   
5351              - r2 = {'500': -0.000016676911302, '600': 0.036594127620440, '800': 2.131014839635728}, 
5352              - pA = 0.936911090448340, 
5353              - dw = 4.325314846914845, 
5354              - dwH = -0.213870168665628, 
5355              - kex = 487.361914835074117, 
5356              - chi2 = 14.870371897291138. 
5357          """ 
5358   
5359          # Base data setup. 
5360          self.setup_korzhnev_2005_data(data_list=['1H MQ']) 
5361   
5362          # Alias the spin. 
5363          spin = return_spin(":9@N") 
5364   
5365          # The R20 keys. 
5366          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5367          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5368          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5369   
5370          # Set the initial parameter values. 
5371          spin.r2 = {r20_key1: 0.000022585022901, r20_key2: 0.039223196112941, r20_key3: 2.136576686700357} 
5372          spin.pA = 0.936884348941701 
5373          spin.dw = 4.326454531583964 
5374          spin.dwH = -0.214026093221782 
5375          spin.kex = 487.043592705469223 
5376   
5377          # Low precision optimisation. 
5378          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=100) 
5379   
5380          # Monte Carlo simulations. 
5381          self.interpreter.monte_carlo.setup(number=3) 
5382          self.interpreter.monte_carlo.create_data(method='back_calc') 
5383          self.interpreter.monte_carlo.initial_values() 
5384          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5385          self.interpreter.monte_carlo.error_analysis() 
5386   
5387          # Plot the dispersion curves. 
5388          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5389   
5390          # Save the results. 
5391          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5392   
5393          # Printout. 
5394          print("\n\nOptimised parameters:\n") 
5395          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5396          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5397          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5398          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5399          print("%-20s %20.15g" % ("pA", spin.pA)) 
5400          print("%-20s %20.15g" % ("dw", spin.dw)) 
5401          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5402          print("%-20s %20.15g" % ("kex", spin.kex)) 
5403          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5404   
5405          # Checks for residue :9. 
5406          self.assertAlmostEqual(spin.r2[r20_key1], 2.48493199969936e-05, 4) 
5407          self.assertAlmostEqual(spin.r2[r20_key2], 0.0382382195911849, 2) 
5408          self.assertAlmostEqual(spin.r2[r20_key3], 2.13397221524655, 2) 
5409          self.assertAlmostEqual(spin.pA, 0.936879359956996, 4) 
5410          self.assertAlmostEqual(spin.dw, 4.32573362253701, 2) 
5411          self.assertAlmostEqual(spin.dwH, -0.213951762275293, 2) 
5412          self.assertAlmostEqual(spin.kex/1000, 487.021196851596/1000, 4) 
5413          self.assertAlmostEqual(spin.chi2, 14.8704048958378, 2) 
5414   
5415   
5416 -    def test_korzhnev_2005_1h_sq_data(self): 
5417          """Optimisation of the Korzhnev et al., 2005 1H SQ CPMG data using the 'NS MMQ 2-site' model. 
5418   
5419          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5420   
5421          Here only the 1H SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5422   
5423              - r2 = {'500': 6.691697587650816, '600': 6.998915158708793, '800': 5.519267837559072}, 
5424              - pA = 0.946949480545876, 
5425              - dwH = -0.265279672133308, 
5426              - kex = 406.548178869750700, 
5427              - chi2 = 50.400680290545026. 
5428          """ 
5429   
5430          # Base data setup. 
5431          self.setup_korzhnev_2005_data(data_list=['1H SQ']) 
5432   
5433          # Alias the spin. 
5434          spin = return_spin(":9@N") 
5435   
5436          # The R20 keys. 
5437          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5438          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5439          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5440   
5441          # Set the initial parameter values. 
5442          spin.r2 = {r20_key1: 6.69107911078939, r20_key2: 6.99888898689085, r20_key3: 5.52012880268077} 
5443          spin.pA = 0.946990967372467 
5444          spin.dwH = -0.265308128403529 
5445          spin.kex = 406.843250675648 
5446   
5447          # Low precision optimisation. 
5448          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5449   
5450          # Monte Carlo simulations. 
5451          self.interpreter.monte_carlo.setup(number=3) 
5452          self.interpreter.monte_carlo.create_data(method='back_calc') 
5453          self.interpreter.monte_carlo.initial_values() 
5454          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5455          self.interpreter.monte_carlo.error_analysis() 
5456   
5457          # Plot the dispersion curves. 
5458          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5459   
5460          # Save the results. 
5461          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5462   
5463          # Printout. 
5464          print("\n\nOptimised parameters:\n") 
5465          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5466          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5467          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5468          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5469          print("%-20s %20.15g" % ("pA", spin.pA)) 
5470          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5471          print("%-20s %20.15g" % ("kex", spin.kex)) 
5472          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5473   
5474          # Checks for residue :9. 
5475          self.assertAlmostEqual(spin.r2[r20_key1], 6.69168251154302, 2) 
5476          self.assertAlmostEqual(spin.r2[r20_key2], 6.99900388754043, 2) 
5477          self.assertAlmostEqual(spin.r2[r20_key3], 5.51921590064843, 2) 
5478          self.assertAlmostEqual(spin.pA, 0.946951877648819, 4) 
5479          self.assertAlmostEqual(spin.dwH, -0.265280175525516, 3) 
5480          self.assertAlmostEqual(spin.kex/1000, 406.566453278183/1000, 2) 
5481          self.assertAlmostEqual(spin.chi2, 50.4006836222044, 1) 
5482   
5483   
5484 -    def test_korzhnev_2005_all_data(self): 
5485          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5486   
5487          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5488   
5489          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5490   
5491              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5492                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5493                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5494                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5495                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5496                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5497              - pA = 0.943125351763911, 
5498              - dw = 4.421827493809807, 
5499              - dwH = -0.272637034755752, 
5500              - kex = 360.609744568697238, 
5501              - chi2 = 162.589570340050813. 
5502          """ 
5503   
5504          # Base data setup. 
5505          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5506   
5507          # Alias the spin. 
5508          spin = return_spin(":9@N") 
5509   
5510          # The R20 keys. 
5511          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5512          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5513          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5514          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5515          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5516          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5517          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5518          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5519          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5520          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5521          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5522          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5523          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5524          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5525          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5526          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5527          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5528          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5529   
5530          # Set the initial parameter values. 
5531          spin.r2 = { 
5532              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5533              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5534              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5535              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5536              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5537              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5538          } 
5539          spin.pA = 0.943129019477673 
5540          spin.dw = 4.42209952545181 
5541          spin.dwH = -0.27258970590969 
5542          spin.kex = 360.516132791038 
5543   
5544          # Low precision optimisation. 
5545          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=10) 
5546   
5547          # Monte Carlo simulations. 
5548          self.interpreter.monte_carlo.setup(number=3) 
5549          self.interpreter.monte_carlo.create_data(method='back_calc') 
5550          self.interpreter.monte_carlo.initial_values() 
5551          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5552          self.interpreter.monte_carlo.error_analysis() 
5553   
5554          # Plot the dispersion curves. 
5555          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5556   
5557          # Save the results. 
5558          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5559   
5560          # Printout. 
5561          print("\n\nOptimised parameters:\n") 
5562          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5563          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5564          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5565          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5566          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5567          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5568          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5569          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5570          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5571          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5572          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5573          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5574          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5575          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5576          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5577          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5578          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5579          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5580          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5581          print("%-20s %20.15g" % ("pA", spin.pA)) 
5582          print("%-20s %20.15g" % ("dw", spin.dw)) 
5583          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5584          print("%-20s %20.15g" % ("kex", spin.kex)) 
5585          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5586   
5587          # Checks for residue :9. 
5588          self.assertAlmostEqual(spin.r2[r20_key1],  6.67288025927458, 4) 
5589          self.assertAlmostEqual(spin.r2[r20_key2],  6.98951408255098, 4) 
5590          self.assertAlmostEqual(spin.r2[r20_key3],  5.52959273852704, 4) 
5591          self.assertAlmostEqual(spin.r2[r20_key4],  8.39471048876782, 4) 
5592          self.assertAlmostEqual(spin.r2[r20_key5],  8.89290699178799, 4) 
5593          self.assertAlmostEqual(spin.r2[r20_key6],  10.4077068723693, 4) 
5594          self.assertAlmostEqual(spin.r2[r20_key7],  5.93611174376373, 4) 
5595          self.assertAlmostEqual(spin.r2[r20_key8],  6.71735669582514, 4) 
5596          self.assertAlmostEqual(spin.r2[r20_key9],  6.83835225518265, 4) 
5597          self.assertAlmostEqual(spin.r2[r20_key10], 8.59615074668922, 4) 
5598          self.assertAlmostEqual(spin.r2[r20_key11], 10.6512137889291, 4) 
5599          self.assertAlmostEqual(spin.r2[r20_key12], 12.5710822919109, 4) 
5600          self.assertAlmostEqual(spin.r2[r20_key13], 7.85956711501608, 4) 
5601          self.assertAlmostEqual(spin.r2[r20_key14], 8.41891642907918, 4) 
5602          self.assertAlmostEqual(spin.r2[r20_key15], 11.2362089223038, 4) 
5603          self.assertAlmostEqual(spin.r2[r20_key16], 9.1965486378935, 4) 
5604          self.assertAlmostEqual(spin.r2[r20_key17], 9.86031627358462, 4) 
5605          self.assertAlmostEqual(spin.r2[r20_key18], 11.9752375592575, 4) 
5606          self.assertAlmostEqual(spin.pA, 0.943129019477673, 4) 
5607          self.assertAlmostEqual(spin.dw, 4.42209952545181, 4) 
5608          self.assertAlmostEqual(spin.dwH, -0.27258970590969, 4) 
5609          self.assertAlmostEqual(spin.kex/1000, 360.516132791038/1000, 4) 
5610          self.assertAlmostEqual(spin.chi2/1000, 162.596331278669/1000, 3) 
5611   
5612   
5613 -    def test_korzhnev_2005_all_data_disp_speed_bug(self): 
5614          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5615   
5616          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5617   
5618          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5619   
5620              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5621                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5622                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5623                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5624                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5625                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5626              - pA = 0.943125351763911, 
5627              - dw = 4.421827493809807, 
5628              - dwH = -0.272637034755752, 
5629              - kex = 360.609744568697238, 
5630              - chi2 = 162.589570340050813. 
5631          """ 
5632   
5633          # Base data setup. 
5634          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5635   
5636          # Alias the spin. 
5637          spin = return_spin(":9@N") 
5638   
5639          # The R20 keys. 
5640          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5641          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5642          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5643          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5644          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5645          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5646          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5647          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5648          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5649          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5650          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5651          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5652          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5653          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5654          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5655          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5656          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5657          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5658   
5659          # Set the initial parameter values. 
5660          spin.r2 = { 
5661              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5662              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5663              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5664              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5665              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5666              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5667          } 
5668          spin.pA = 0.943129019477673 
5669          spin.dw = 4.42209952545181 
5670          spin.dwH = -0.27258970590969 
5671          spin.kex = 360.516132791038 
5672   
5673          # Calc the chi2 values at these parameters. 
5674          self.interpreter.minimise.calculate(verbosity=1) 
5675   
5676          # Printout. 
5677          print("\n\nOptimised parameters:\n") 
5678          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5679          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5680          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5681          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5682          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5683          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5684          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5685          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5686          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5687          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5688          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5689          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5690          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5691          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5692          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5693          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5694          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5695          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5696          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5697          print("%-20s %20.15g" % ("pA", spin.pA)) 
5698          print("%-20s %20.15g" % ("dw", spin.dw)) 
5699          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5700          print("%-20s %20.15g" % ("kex", spin.kex)) 
5701          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5702   
5703          # Checks for residue :9. 
5704          self.assertAlmostEqual(spin.chi2/1000, 162.511988511609/1000, 3) 
5705   
5706   
5707 -    def test_kteilum_fmpoulsen_makke_check_graphs(self): 
5708          """Check of all possible dispersion graphs from optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5709   
5710          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5711   
5712          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5713   
5714            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5715            - 0.483 0.89623903 2.4503699912708878 
5716            - 0.545 1.1694838 
5717            - 0.545 1.1761503 
5718            - 0.622 1.294 
5719            - 0.669 1.5176493 
5720            - 0.722 1.6238791 
5721            - 0.813 1.9395758 
5722            - 1.011 2.3558415 10.547000429321157 
5723          """ 
5724   
5725          # Base data setup. 
5726          model = 'TSMFK01' 
5727          expfolder = "acbp_cpmg_disp_048MGuHCl_40C_041223" 
5728          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model=model, expfolder=expfolder) 
5729   
5730          # Alias the spins. 
5731          res61L = cdp.mol[0].res[0].spin[0] 
5732   
5733          # The R20 keys. 
5734          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5735   
5736          # Set the initial parameter values. 
5737          res61L.r2a = {r20_key1: 8.0} 
5738          res61L.dw = 6.5 
5739          res61L.k_AB = 2.5 
5740   
5741          # Low precision optimisation. 
5742          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5743   
5744          # Start testing all possible combinations of graphs. 
5745          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
5746          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
5747          interpolate_types = [INTERPOLATE_DISP] 
5748   
5749          # Write to temp folder. 
5750          result_dir_name = ds.tmpdir 
5751          result_folders = [model] 
5752          spin_id = ":61@N" 
5753   
5754          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
5755          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder+sep+'check_graphs' 
5756   
5757          for result_folder in result_folders: 
5758              for y_axis in y_axis_types: 
5759                  for x_axis in x_axis_types: 
5760                      for interpolate in interpolate_types: 
5761                          # Determine file name: 
5762                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
5763   
5764                          # Make the file name. 
5765                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
5766   
5767                          # Write the curves. 
5768                          dir = result_dir_name+sep+result_folder 
5769                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
5770                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
5771   
5772                          # Get the file path. 
5773                          file_path = get_file_path(file_name, dir) 
5774   
5775                          # Test the plot file exists. 
5776                          print("Testing file access to graph: %s"%file_path) 
5777                          self.assert_(access(file_path, F_OK)) 
5778   
5779                          # Now open, and compare content, line by line. 
5780                          file_prod = open(file_path) 
5781                          lines_prod = file_prod.readlines() 
5782                          file_prod.close() 
5783   
5784                          # Define file to compare against. 
5785                          dir_comp = data_path+sep+result_folder 
5786                          file_path_comp = get_file_path(file_name, dir_comp) 
5787                          file_comp = open(file_path_comp) 
5788                          lines_comp = file_comp.readlines() 
5789                          file_comp.close() 
5790   
5791                          ## Assert number of lines is equal. 
5792                          self.assertEqual(len(lines_prod), len(lines_comp)) 
5793                          for j in range(len(lines_prod)): 
5794                              # Make the string test 
5795                              first_char = lines_prod[j][0] 
5796                              if first_char in ["@", "&"]: 
5797                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
5798                              else: 
5799                                  # Split string in x, y, error. 
5800                                  # The error would change per run. 
5801                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
5802                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
5803                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
5804                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
5805                                  self.assertAlmostEqual(float(y_prod_err), float(y_comp_err)) 
5806   
5807   
5808 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72(self): 
5809          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5810   
5811          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5812          """ 
5813   
5814          # Base data setup. 
5815          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5816   
5817          # Alias the spins. 
5818          res61L = cdp.mol[0].res[0].spin[0] 
5819   
5820          # The R20 keys. 
5821          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5822   
5823          # Set the initial parameter values. 
5824          res61L.r2 = {r20_key1: 8.0} 
5825          res61L.pA = 0.9 
5826          res61L.dw = 6.0 
5827          res61L.kex = 600.0 
5828   
5829          # Low precision optimisation. 
5830          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5831   
5832          # Printout. 
5833          print("\n\nOptimised parameters:\n") 
5834          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5835          print("%-20s %20.15g" % ("R2 (600 MHz)", res61L.r2[r20_key1])) 
5836          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5837          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5838          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5839          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5840   
5841          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5842          self.assertAlmostEqual(res61L.r2[r20_key1], 8.69277980194016, 4) 
5843          self.assertAlmostEqual(res61L.pA, 0.9943781590842946, 5) 
5844          self.assertAlmostEqual(res61L.dw, 6.389453131263374, 3) 
5845          self.assertAlmostEqual(res61L.kex, 609.262167216419, 0) 
5846          self.assertAlmostEqual(res61L.chi2, 65.99987828889657, 5) 
5847   
5848          # Test the conversion to k_AB from kex and pA. 
5849          self.assertEqual(res61L.k_AB, res61L.kex * (1.0 - res61L.pA)) 
5850   
5851          # Test the conversion to k_BA from kex and pA. 
5852          self.assertEqual(res61L.k_BA, res61L.kex * res61L.pA) 
5853   
5854   
5855 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72_full(self): 
5856          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5857   
5858          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5859          """ 
5860   
5861          # Base data setup. 
5862          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72 full', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5863   
5864          # Alias the spins. 
5865          res61L = cdp.mol[0].res[0].spin[0] 
5866   
5867          # The R20 keys. 
5868          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5869   
5870          # Set the initial parameter values. 
5871          res61L.r2a = {r20_key1: 8.0} 
5872          res61L.r2b = {r20_key1: 105.0} 
5873          res61L.pA = 0.9 
5874          res61L.dw = 6.0 
5875          res61L.kex = 500.0 
5876   
5877          # Low precision optimisation. 
5878          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5879   
5880          # Printout. 
5881          print("\n\nOptimised parameters:\n") 
5882          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5883          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5884          print("%-20s %20.15g" % ("R2B (600 MHz)", res61L.r2b[r20_key1])) 
5885          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5886          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5887          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5888          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5889   
5890          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5891          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.044428899438309, 0) 
5892          self.assertAlmostEqual(res61L.r2b[r20_key1], 105.11894506392449, -2) 
5893          self.assertAlmostEqual(res61L.pA, 0.992066883657578, 2) 
5894          self.assertAlmostEqual(res61L.dw, 6.389453586338883, 3) 
5895          self.assertAlmostEqual(res61L.kex, 513.483608742063, -2) 
5896          self.assertAlmostEqual(res61L.chi2, 65.99987828890289, 5) 
5897   
5898   
5899 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_tsmfk01(self): 
5900          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5901   
5902          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5903   
5904          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5905   
5906            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5907            - 0.483 0.89623903 2.4503699912708878 
5908            - 0.545 1.1694838 
5909            - 0.545 1.1761503 
5910            - 0.622 1.294 
5911            - 0.669 1.5176493 
5912            - 0.722 1.6238791 
5913            - 0.813 1.9395758 
5914            - 1.011 2.3558415 10.547000429321157 
5915          """ 
5916   
5917          # Base data setup. 
5918          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5919   
5920          # Alias the spins. 
5921          res61L = cdp.mol[0].res[0].spin[0] 
5922   
5923          # The R20 keys. 
5924          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5925   
5926          # Set the initial parameter values. 
5927          res61L.r2a = {r20_key1: 8.0} 
5928          res61L.dw = 6.5 
5929          res61L.k_AB = 2.5 
5930   
5931          # Low precision optimisation. 
5932          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5933   
5934          # Printout. 
5935          print("\n\nOptimised parameters:\n") 
5936          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5937          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5938          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5939          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5940          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5941   
5942          # Checks for residue :61. Reference values from paper 
5943   
5944          self.assertAlmostEqual(res61L.k_AB, 2.45, 1) 
5945   
5946   
5947 -    def test_kteilum_fmpoulsen_makke_cpmg_data_101m_guhcl_to_tsmfk01(self): 
5948          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5949   
5950          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 1.01 M GuHCl (guanidine hydrochloride). 
5951   
5952          The comparison is to Figure 2, which is for dataset with 1 M GuHCl.  The reported results are expected to be in rad.s^-1.  Conversion into relax stored values is preferably. 
5953   
5954          Representative 15N CPMG relaxation dispersion curve measured on the cross peaks from residue L61 in folded ACBP at pH 5.3, 1 M GuHCl, and 40C: 
5955   
5956            1. The dotted line represents a residue-specific fit of all parameters in Eq. 1: 
5957              - k_AB = 11.3 +/- 0.7 s^-1, 
5958              - dw = (2.45 +/- 0.09) * 10^3 s^-1, 
5959              - R2 = 8.0 +/- 0.5 s^-1. 
5960   
5961            2. The solid line represents a global fit of k_AB to all protein residues and a residue-specific fit of dw and R2.: 
5962              - k_AB = 10.55 +/- 0.08 s^-1, 
5963              - dw = (2.44 +/- 0.08) * 10^3 s^-1, 
5964              - R2 = 8.4 +/- 0.3 s^-1. 
5965   
5966          Conversion of paper results to relax results is performed by: 
5967   
5968            - dw(ppm) = dw(rad.s^-1) * 10^6 * 1/(2*pi) * (gyro1H/(gyro15N*spectrometer_freq)) = 2.45E3 * 1E6 / (2 * math.pi) * (26.7522212E7/(-2.7126E7 * 599.8908622E6)) = -6.41 ppm. 
5969   
5970          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl.  The precise values are: 
5971   
5972            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5973            - 0.483 0.89623903 2.4503699912708878 
5974            - 0.545 1.1694838 
5975            - 0.545 1.1761503 
5976            - 0.622 1.294 
5977            - 0.669 1.5176493 
5978            - 0.722 1.6238791 
5979            - 0.813 1.9395758 
5980            - 1.011 2.3558415 10.547000429321157 
5981          """ 
5982   
5983          # Base data setup. 
5984          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_101MGuHCl_40C_041223") 
5985   
5986          # Alias the spins. 
5987          res61L = cdp.mol[0].res[0].spin[0] 
5988   
5989          # The R20 keys. 
5990          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086270e6) 
5991   
5992          # Set the initial parameter values. 
5993          res61L.r2a = {r20_key1: 8.0} 
5994          res61L.dw = 6.5 
5995          res61L.k_AB = 11.0 
5996   
5997          # Low precision optimisation. 
5998          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5999   
6000          # Printout. 
6001          print("\n\nOptimised parameters:\n") 
6002          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
6003          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
6004          print("%-20s %20.15g" % ("dw", res61L.dw)) 
6005          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
6006          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
6007   
6008          # Checks for residue :61. Reference values from paper 
6009   
6010          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.4, 0) 
6011          self.assertAlmostEqual(res61L.dw, 6.41, 0) 
6012          self.assertAlmostEqual(res61L.k_AB, 10.55, 0) 
6013   
6014   
6015 -    def test_lm63_3site_synthetic(self): 
6016          """Test the 'LM63 3-site' dispersion model using the pure noise-free synthetic data.""" 
6017   
6018          # The path to the data files. 
6019          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'lm63_3site' 
6020   
6021          # Load the state file. 
6022          self.interpreter.reset() 
6023          self.interpreter.state.load(data_path+sep+'r2eff_values') 
6024   
6025          # A new data pipe. 
6026          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='LM63 3-site', bundle_to='relax_disp') 
6027          self.interpreter.pipe.switch(pipe_name='LM63 3-site') 
6028   
6029          # Set up the model data. 
6030          self.interpreter.relax_disp.select_model(model='LM63 3-site') 
6031          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='LM63 3-site', param='r2eff') 
6032          self.interpreter.spin.isotope('15N') 
6033   
6034          # Alias the spins. 
6035          spin1 = return_spin(":1") 
6036          spin2 = return_spin(":2") 
6037   
6038          # The R20 keys. 
6039          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
6040          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
6041   
6042          # Manually set the parameter values. 
6043          spin1.r2 = {r20_key1: 12.0, r20_key2: 12.0} 
6044          spin1.phi_ex_B = 0.1 
6045          spin1.phi_ex_C = 0.5 
6046          spin1.kB = 1500.0 
6047          spin1.kC = 2500.0 
6048          spin2.r2 = {r20_key1: 15.0, r20_key2: 15.0} 
6049          spin2.phi_ex_B = 0.1 
6050          spin2.phi_ex_C = 0.5 
6051          spin2.kB = 1500.0 
6052          spin2.kC = 2500.0 
6053   
6054          # Low precision optimisation. 
6055          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
6056   
6057          # Monte Carlo simulations. 
6058          self.interpreter.monte_carlo.setup(number=3) 
6059          self.interpreter.monte_carlo.create_data(method='back_calc') 
6060          self.interpreter.monte_carlo.initial_values() 
6061          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-2, grad_tol=None, max_iter=10, constraints=True, scaling=True, verbosity=1) 
6062          self.interpreter.monte_carlo.error_analysis() 
6063   
6064          # Save the results. 
6065          self.interpreter.results.write(file='devnull', compress_type=1, force=True) 
6066   
6067          # The model checks. 
6068          print("\n\nOptimised parameters:\n") 
6069          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
6070          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
6071          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
6072          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin1.phi_ex_B, spin2.phi_ex_B)) 
6073          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin1.phi_ex_C, spin2.phi_ex_C)) 
6074          print("%-20s %20.15g %20.15g" % ("kB", spin1.kB, spin2.kB)) 
6075          print("%-20s %20.15g %20.15g" % ("kC", spin1.kC, spin2.kC)) 
6076          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
6077          self.assertAlmostEqual(spin1.r2[r20_key1], 12.0, 2) 
6078          self.assertAlmostEqual(spin1.r2[r20_key2], 12.0, 2) 
6079          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
6080          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
6081          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
6082          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
6083          self.assertAlmostEqual(spin1.chi2, 0.0, 3) 
6084          self.assertAlmostEqual(spin2.r2[r20_key1], 15.0, 3) 
6085          self.assertAlmostEqual(spin2.r2[r20_key2], 15.0, 3) 
6086          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
6087          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
6088          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
6089          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
6090          self.assertAlmostEqual(spin2.chi2, 0.0, 3) 
6091   
6092   
6093 -    def test_m61_data_to_m61(self): 
6094          """Test the relaxation dispersion 'M61' model curve fitting to fixed time synthetic data.""" 
6095   
6096          # Fixed time variable. 
6097          ds.fixed = True 
6098   
6099          # Execute the script. 
6100          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6101   
6102          # The original parameters. 
6103          i0 = [100000.0, 20000.0] 
6104          r1rho_prime = [2.25, 24.0] 
6105          pA = 0.7 
6106          kex = 1000.0 
6107          delta_omega = [1.0, 2.0] 
6108          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6109          phi_ex = [] 
6110          for i in range(2): 
6111              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6112          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6113   
6114          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6115          self.interpreter.pipe.switch('R2eff - relax_disp') 
6116          spin_index = 0 
6117          for spin, spin_id in spin_loop(return_id=True): 
6118              # Printout. 
6119              print("\nSpin %s." % spin_id) 
6120   
6121              # Check the fitted parameters. 
6122              for i in range(len(keys)): 
6123                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6124   
6125              # Increment the spin index. 
6126              spin_index += 1 
6127   
6128          # The R20 keys. 
6129          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6130   
6131          # Switch to the 'M61' model data pipe, then check for each spin. 
6132          self.interpreter.pipe.switch('M61 - relax_disp') 
6133          spin_index = 0 
6134          for spin, spin_id in spin_loop(return_id=True): 
6135              # Printout. 
6136              print("\nSpin %s." % spin_id) 
6137   
6138              # Check the fitted parameters. 
6139              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6140              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6141              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6142   
6143              # Increment the spin index. 
6144              spin_index += 1 
6145   
6146   
6147 -    def test_m61_exp_data_to_m61(self): 
6148          """Test the relaxation dispersion 'M61' model curve fitting to the full exponential synthetic data.""" 
6149   
6150          # Fixed time variable. 
6151          ds.fixed = False 
6152   
6153          # Single spin optimisation. 
6154          ds.single = True 
6155   
6156          # Execute the script. 
6157          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6158   
6159          # The original parameters. 
6160          i0 = [100000.0, 20000.0] 
6161          r1rho_prime = [2.25, 24.0] 
6162          pA = 0.7 
6163          kex = 1000.0 
6164          delta_omega = [1.0, 2.0] 
6165          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6166          phi_ex = [] 
6167          for i in range(2): 
6168              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6169          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6170   
6171          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6172          self.interpreter.pipe.switch('R2eff - relax_disp') 
6173          spin_index = 0 
6174          for spin, spin_id in spin_loop(return_id=True): 
6175              # Printout. 
6176              print("\nSpin %s." % spin_id) 
6177   
6178              # Check the fitted parameters. 
6179              for i in range(len(keys)): 
6180                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6181   
6182              # Increment the spin index. 
6183              spin_index += 1 
6184   
6185          # The R20 keys. 
6186          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6187   
6188          # Switch to the 'M61' model data pipe, then check for each spin. 
6189          self.interpreter.pipe.switch('M61 - relax_disp') 
6190          spin_index = 0 
6191          for spin, spin_id in spin_loop(return_id=True): 
6192              # Printout. 
6193              print("\nSpin %s." % spin_id) 
6194   
6195              # Check the fitted parameters. 
6196              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6197              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6198              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6199   
6200              # Increment the spin index. 
6201              spin_index += 1 
6202   
6203   
6204 -    def test_m61b_data_to_m61b(self): 
6205          """Test the relaxation dispersion 'M61 skew' model curve fitting to fixed time synthetic data.""" 
6206   
6207          # Execute the script. 
6208          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61b.py') 
6209   
6210          # The original parameters. 
6211          i0 = [100000.0, 20000.0] 
6212          r1rho_prime = [10.0, 24.0] 
6213          pA = 0.95 
6214          kex = 2000.0 
6215          delta_omega = [1.0, 2.0] 
6216   
6217          # The R20 keys. 
6218          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6219   
6220          # Switch to the 'M61 skew' model data pipe, then check for each spin. 
6221          self.interpreter.pipe.switch("%s - relax_disp" % MODEL_M61B) 
6222          spin_index = 0 
6223          for spin, spin_id in spin_loop(return_id=True): 
6224              # Printout. 
6225              print("\nSpin %s." % spin_id) 
6226   
6227              # Check the fitted parameters. 
6228              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6229              self.assertAlmostEqual(spin.pA, pA, 2) 
6230              self.assertAlmostEqual(spin.dw, dw[spin_index], 2) 
6231              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6232   
6233              # Increment the spin index. 
6234              spin_index += 1 
6235   
6236   
6237 -    def test_model_nesting_and_param(self): 
6238          """Test that all models which can nest, have all their parameters converted.""" 
6239   
6240          # Set the experiment type. 
6241          cdp.exp_type_list = EXP_TYPE_LIST 
6242   
6243          # Get info for all models. 
6244          all_models_info = models_info(models=MODEL_LIST_FULL) 
6245   
6246          # Loop over all models. 
6247          print("Printing the listed of nested models for each model.") 
6248          print("#########################################") 
6249          for model_info in all_models_info: 
6250              print("%s"%model_info.model), 
6251              print("<-"), 
6252              nest_list = model_info.nest_list 
6253              if nest_list == None: 
6254                  nest_list = ["None"] 
6255              print(', '.join(map(str, nest_list))) 
6256   
6257              # Skip if there is no model to nest from. 
6258              if nest_list == ["None"]: 
6259                  continue 
6260   
6261              # Assign params to variable. 
6262              model_params = model_info.params 
6263   
6264              # Now loop over the nested models. 
6265              for nested_model in nest_list: 
6266                  # Get the params for the nested model. 
6267                  nested_model_params = MODEL_PARAMS[nested_model] 
6268   
6269                  # Get the dictionary of parameter conversion. 
6270                  par_dic = nesting_param(model_params=model_params, nested_model_params=nested_model_params) 
6271   
6272                  # Test the number of elements in the dictionary. 
6273                  self.assertEqual(len(par_dic), len(model_params)) 
6274   
6275                  # Loop over dictionary. 
6276                  for param in par_dic: 
6277                          if param != par_dic[param]: 
6278                              print("Model:'%s', Nested model:'%s', Copying '%s' to '%s'." % (model_info.model, nested_model, par_dic[param], param)) 
6279                          self.assertNotEqual(par_dic[param], None) 
6280   
6281   
6282 -    def test_ns_mmq_3site(self): 
6283          """Compare the 'NS MMQ 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6284   
6285          # Execute the script. 
6286          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site.py') 
6287   
6288          # Check the chi-squared value. 
6289          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6290   
6291   
6292 -    def test_ns_mmq_3site_linear(self): 
6293          """Compare the 'NS MMQ 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6294   
6295          # Execute the script. 
6296          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site_linear.py') 
6297   
6298          # Check the chi-squared value. 
6299          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6300   
6301   
6302 -    def test_ns_r1rho_3site(self): 
6303          """Compare the 'NS R1rho 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6304   
6305          # Execute the script. 
6306          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site.py') 
6307   
6308          # Check the chi-squared value. 
6309          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 136.13141468674999, 3) 
6310   
6311   
6312 -    def test_ns_r1rho_3site_linear(self): 
6313          """Compare the 'NS R1rho 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6314   
6315          # Execute the script. 
6316          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site_linear.py') 
6317   
6318          # Check the chi-squared value. 
6319          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 0.030959849811015544, 3) 
6320   
6321   
6322 -    def test_repeat_cpmg(self): 
6323          """Test the protocol for repeated dispersion analysis. The class: relax_disp_repeat_cpmg. 
6324   
6325          U{task #7826<https://gna.org/task/index.php?7826>}. Write an python class for the repeated analysis of dispersion data. 
6326          """ 
6327   
6328          # Reset. 
6329          self.interpreter.reset() 
6330   
6331          # Define base path to files. 
6332          base_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1' 
6333   
6334          # Setup dictionary with settings. 
6335          sdic = {} 
6336           
6337          # Spectrometer frqs in list. 
6338          sfrq_1 = 499.86214 
6339          sfrq_2 = 599.8908587 
6340          sfrqs = [sfrq_1, sfrq_2] 
6341           
6342          # Store in dictionary. 
6343          sdic['sfrqs'] = sfrqs 
6344           
6345          # Store unit for frq. 
6346          sdic['sfrq_unit'] = 'MHz' 
6347           
6348          # Store exp_type 
6349          sdic['exp_type'] = 'SQ CPMG' 
6350   
6351          # Store spin isotope 
6352          sdic['isotope'] = '15N' 
6353   
6354          # How intensity was measured. 
6355          sdic['int_method'] = 'height' 
6356   
6357          # Define the time for result directory. 
6358          sdic['time'] = '2014_09' 
6359   
6360          # Initialize frq dics. 
6361          for frq in sfrqs: 
6362              key = DIC_KEY_FORMAT % (frq) 
6363              sdic[key] = {} 
6364           
6365          # Set keys. 
6366          e_1 = DIC_KEY_FORMAT % (sfrq_1) 
6367          e_2 = DIC_KEY_FORMAT % (sfrq_2) 
6368           
6369          # Store time T2. 
6370          sdic[e_1]['time_T2'] = 0.04 
6371          sdic[e_2]['time_T2'] = 0.06 
6372           
6373          # Set ncyc. 
6374          ncyc_1 = array([20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0]) 
6375          ncyc_2 = array([28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 52, 18, 40, 6, 12, 0, 24, 14, 22]) 
6376   
6377          # Calculate the cpmg_frq and store. 
6378          sdic[e_1]['cpmg_frqs'] = ncyc_1 / sdic[e_1]['time_T2'] 
6379          sdic[e_2]['cpmg_frqs'] = ncyc_2 / sdic[e_2]['time_T2'] 
6380           
6381          # Define peak lists. 
6382          peaks_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files' 
6383          peaks_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files'  
6384          sdic[e_1]['peaks_folder'] = peaks_folder_1 
6385          sdic[e_2]['peaks_folder'] = peaks_folder_2 
6386           
6387          # Define folder to all rmsd files. 
6388          rmsd_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'ft2_data' 
6389          rmsd_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'ft2_data' 
6390          sdic[e_1]['rmsd_folder'] = rmsd_folder_1  
6391          sdic[e_2]['rmsd_folder'] = rmsd_folder_2 
6392   
6393          # Define temporary folder. 
6394          sdic['results_dir'] = self.tmpdir 
6395   
6396          # Setup class with data. 
6397          RDR =  Relax_disp_rep(sdic) 
6398   
6399          # Setup base information. 
6400          RDR.set_base_cpmg(method='FT', glob_ini=128) 
6401   
6402          methods = ['FT', 'MDD'] 
6403          #methods = ['FT'] 
6404   
6405          # Set the intensity. 
6406          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=False, set_rep=True) 
6407          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=True, set_rep=False) 
6408   
6409          # Try plot some intensity correlations. 
6410          if True: 
6411              selection = None 
6412   
6413              # Now make a spin selection. 
6414              int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128, 126], selection=selection) 
6415   
6416              # For mdd 
6417              int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6418   
6419              # Plot correlation of intensity 
6420              fig1 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6421              fig2 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6422              corr_data = [fig1, fig2] 
6423   
6424              write_stats = True 
6425              RDR.plot_int_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6426   
6427              # Open stat file. 
6428              if write_stats: 
6429                  for i, corr_data_i in enumerate(corr_data): 
6430                      data, methods, glob_inis = corr_data[i] 
6431                      data_x, data_y = data 
6432                      method_x, method_y = methods 
6433                      glob_ini_x, glob_ini_y = glob_inis 
6434                      x = data_x[str(glob_ini_x)]['peak_intensity_arr'] 
6435                      np = len(x) 
6436   
6437                      file_name_ini = 'int_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6438   
6439                      if selection == None: 
6440                          file_name = file_name_ini + '_all.txt' 
6441                      else: 
6442                          file_name = file_name_ini + '_sel.txt' 
6443                      path = RDR.results_dir 
6444                      data = extract_data(file=file_name, dir=path) 
6445   
6446                      # Loop over the lines. 
6447                      for i, data_i in enumerate(data): 
6448                          print(i, data_i) 
6449   
6450   
6451          # Try plot some intensity statistics. 
6452          if True: 
6453              # Collect r2eff values. 
6454              selections = [None, ':2,3'] 
6455              for selection in selections: 
6456                  int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128], selection=selection) 
6457                  int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6458   
6459                  # Get R2eff stats. 
6460                  int_stat_dic = RDR.get_int_stat_dic(list_int_dics=[int_ft_sel, int_mdd_sel], list_glob_ini=[128, 126]) 
6461   
6462                  ## Plot R2eff stats 
6463                  write_stats = True 
6464                  RDR.plot_int_stat(int_stat_dic=int_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126], show=False, write_stats=write_stats) 
6465   
6466                  # Open stat file. 
6467                  if write_stats: 
6468                      if selection == None: 
6469                          file_name = 'int_stat_all.txt' 
6470                      else: 
6471                          file_name = 'int_stat_sel.txt' 
6472                      path = RDR.results_dir 
6473                      data = extract_data(file=file_name, dir=path) 
6474   
6475                      # Loop over the lines. 
6476                      for i, data_i in enumerate(data): 
6477                          print(i, data_i) 
6478   
6479   
6480          # Try write some R2eff correlations. 
6481          if True: 
6482              selection = None 
6483              # Collect r2eff values. 
6484              r2eff_ft_all = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6485   
6486              # For all spins, mdd 
6487              r2eff_mdd_all = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6488   
6489              # Plot correlation of intensity 
6490              fig1 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 128]] 
6491              fig2 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 126]] 
6492              corr_data = [fig1, fig2] 
6493   
6494              write_stats = True 
6495              RDR.plot_r2eff_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6496   
6497              # Open stat file. 
6498              if write_stats: 
6499                  for i, corr_data_i in enumerate(corr_data): 
6500                      data, methods, glob_inis = corr_data[i] 
6501                      data_x, data_y = data 
6502                      method_x, method_y = methods 
6503                      glob_ini_x, glob_ini_y = glob_inis 
6504                      x = data_x[str(glob_ini_x)]['r2eff_arr'] 
6505                      np = len(x) 
6506   
6507                      file_name_ini = 'r2eff_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6508   
6509                      if selection == None: 
6510                          file_name = file_name_ini + '_all.txt' 
6511                      else: 
6512                          file_name = file_name_ini + '_sel.txt' 
6513                      path = RDR.results_dir 
6514                      data = extract_data(file=file_name, dir=path) 
6515   
6516                      # Loop over the lines. 
6517                      for i, data_i in enumerate(data): 
6518                          print(i, data_i) 
6519   
6520   
6521          # Try plot some R2eff statistics. 
6522          if True: 
6523              # Collect r2eff values. 
6524              selections = [None, ':2,3'] 
6525              for selection in selections: 
6526                  r2eff_ft_sel = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6527                  r2eff_mdd_sel = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6528   
6529                  # Get R2eff stats. 
6530                  r2eff_stat_dic = RDR.get_r2eff_stat_dic(list_r2eff_dics=[r2eff_ft_sel, r2eff_mdd_sel], list_glob_ini=[128, 126]) 
6531   
6532                  ## Plot R2eff stats 
6533                  write_stats = True 
6534                  RDR.plot_r2eff_stat(r2eff_stat_dic=r2eff_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6535   
6536                  # Open stat file. 
6537                  if write_stats: 
6538                      if selection == None: 
6539                          file_name = 'r2eff_stat_all.txt' 
6540                      else: 
6541                          file_name = 'r2eff_stat_sel.txt' 
6542                      path = RDR.results_dir 
6543                      data = extract_data(file=file_name, dir=path) 
6544   
6545                      # Loop over the lines. 
6546                      for i, data_i in enumerate(data): 
6547                          print(i, data_i) 
6548   
6549   
6550          # Do minimisation individual. 
6551          if True: 
6552              methods = ['FT', 'MDD'] 
6553              # Now calculate R2eff. 
6554              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6555   
6556              min_methods = [['FT'], ['MDD']] 
6557              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6558   
6559              #min_methods = [['FT']] 
6560              #min_list_glob_ini = [[128]] 
6561              #selection = ':2,3' 
6562              selection = None 
6563   
6564              for i, methods in enumerate(min_methods): 
6565                  list_glob_ini = min_list_glob_ini[i] 
6566   
6567                  if True: 
6568                      # First get data. 
6569                      if True: 
6570                          # First load all data. 
6571                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6572   
6573                      # Then set R20 
6574                      if True: 
6575                          # Set R20 from min R2eff in preparation for Grid search. 
6576                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, model_from=MODEL_R2EFF, analysis='grid_setup_ind', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6577   
6578                      # Check and print parameters. 
6579                      if True: 
6580                          # Print for pipe name 
6581                          method = methods[0] 
6582                          glob_ini = list_glob_ini[0] 
6583   
6584                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup_ind', glob_ini=glob_ini) 
6585                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6586   
6587                      # Then Grid search. 
6588                      if True: 
6589                          # Do Grid search. 
6590                          RDR.minimise_grid_search(inc=4, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6591   
6592                  # Then Minimise. 
6593                  if True: 
6594                      # Minimise 
6595                      RDR.opt_max_iterations = int(1e2) 
6596                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min_ind', analysis_from='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6597   
6598                  #print asd 
6599   
6600          # Plot statistics. 
6601          # Try plot some minimisation correlations. 
6602          if True: 
6603              selections = [None, ':2,3'] 
6604              for selection in selections: 
6605                  # Collect param values. 
6606                  analysis = 'min_ind' 
6607                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6608                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6609   
6610                  fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6611                  fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6612                  corr_data = [fig1, fig2] 
6613   
6614                  write_stats = True 
6615                  RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6616   
6617                  # Open stat file. 
6618                  if write_stats: 
6619                      for i, corr_data_i in enumerate(corr_data): 
6620                          data, methods, glob_inis = corr_data[i] 
6621                          data_x, data_y = data 
6622                          method_x, method_y = methods 
6623                          glob_ini_x, glob_ini_y = glob_inis 
6624   
6625                          file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6626   
6627                          if selection == None: 
6628                              file_name = file_name_ini + '_all.txt' 
6629                          else: 
6630                              file_name = file_name_ini + '_sel.txt' 
6631                          path = RDR.results_dir 
6632                          data = extract_data(file=file_name, dir=path) 
6633   
6634                          # Loop over the lines. 
6635                          for i, data_i in enumerate(data): 
6636                              print(i, data_i) 
6637   
6638          # Try plot some minimisation statistics. 
6639          if True: 
6640              # Collect param values. 
6641              #selections = [None, ':2,3'] 
6642              selections = [None, ':2,3'] 
6643              for selection in selections: 
6644                  analysis = 'min_ind' 
6645                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6646                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6647   
6648                  # Get param stats. 
6649                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6650   
6651                  ## Plot R2eff stats 
6652                  write_stats = True 
6653                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6654   
6655                  # Open stat file. 
6656                  if write_stats: 
6657                      if selection == None: 
6658                          file_name = '%s_stat_all.txt' % (analysis) 
6659                      else: 
6660                          file_name = '%s_stat_sel.txt' % (analysis) 
6661                      path = RDR.results_dir 
6662                      data = extract_data(file=file_name, dir=path) 
6663   
6664                      # Loop over the lines. 
6665                      for i, data_i in enumerate(data): 
6666                          print(i, data_i) 
6667   
6668   
6669          # Do minimisation clustered. 
6670          if True: 
6671              methods = ['FT', 'MDD'] 
6672              # Now calculate R2eff. 
6673              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6674   
6675              min_methods = [['FT'], ['MDD']] 
6676              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6677   
6678              #min_methods = [['FT']] 
6679              #min_list_glob_ini = [[128]] 
6680              selection = ':2,3' 
6681   
6682              for i, methods in enumerate(min_methods): 
6683                  list_glob_ini = min_list_glob_ini[i] 
6684   
6685                  if True: 
6686                      # First get data. 
6687                      if True: 
6688                          # First load all data. 
6689                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6690                       
6691                      # Then select spins. 
6692                      if True: 
6693                          # Deselect all spins. 
6694                          RDR.deselect_all(methods=methods, model='setup', model_from=MODEL_R2EFF, analysis='grid_setup', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6695                   
6696                          RDR.select_spin(spin_id=selection, methods=methods, model='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6697                   
6698                      # Then preset values. 
6699                      if True: 
6700                          # Set k_AB for Grid search. 
6701                          RDR.value_set(methods=methods, val=1000., param='kex', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6702                          RDR.value_set(methods=methods, val=0.95, param='pA', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6703                   
6704                      # Then set R20 
6705                      if True: 
6706                          # Set R20 from min R2eff in preparation for Grid search. 
6707                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6708                   
6709                      # Check and print parameters. 
6710                      if True: 
6711                          # Print for pipe name 
6712                          method = methods[0] 
6713                          glob_ini = list_glob_ini[0] 
6714   
6715                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup', glob_ini=glob_ini) 
6716                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6717                       
6718                      # Then Grid search. 
6719                      if True: 
6720                          # Do Grid search. 
6721                          RDR.minimise_grid_search(inc=200, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid', analysis_from='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6722                   
6723                      # Then cluster spins. 
6724                      if True: 
6725                          RDR.cluster_spins(spin_id=selection, methods=methods, model=MODEL_CR72, analysis='grid', list_glob_ini=list_glob_ini, force=True) 
6726               
6727                  # Then Minimise. 
6728                  if True: 
6729                      # Minimise 
6730                      RDR.opt_max_iterations = int(1e2) 
6731                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min', analysis_from='grid', list_glob_ini=list_glob_ini, force=False) 
6732   
6733          # Plot statistics. 
6734          # Try plot some minimisation correlations. 
6735          if True: 
6736              selection = ':2,3' 
6737              # Collect param values. 
6738              analysis = 'min' 
6739              min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6740              min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6741   
6742              fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6743              fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6744              corr_data = [fig1, fig2] 
6745   
6746              write_stats = True 
6747              RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6748   
6749              # Open stat file. 
6750              if write_stats: 
6751                  for i, corr_data_i in enumerate(corr_data): 
6752                      data, methods, glob_inis = corr_data[i] 
6753                      data_x, data_y = data 
6754                      method_x, method_y = methods 
6755                      glob_ini_x, glob_ini_y = glob_inis 
6756   
6757                      file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6758   
6759                      if selection == None: 
6760                          file_name = file_name_ini + '_all.txt' 
6761                      else: 
6762                          file_name = file_name_ini + '_sel.txt' 
6763                      path = RDR.results_dir 
6764                      data = extract_data(file=file_name, dir=path) 
6765   
6766                      # Loop over the lines. 
6767                      for i, data_i in enumerate(data): 
6768                          print(i, data_i) 
6769   
6770          # Try plot some minimisation statistics. 
6771          if True: 
6772              # Collect param values. 
6773              selections = [':2,3'] 
6774              for selection in selections: 
6775                  analysis = 'min' 
6776                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6777                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6778   
6779                  # Get param stats. 
6780                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6781   
6782                  ## Plot R2eff stats 
6783                  write_stats = True 
6784                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6785   
6786                  # Open stat file. 
6787                  if write_stats: 
6788                      if selection == None: 
6789                          file_name = '%s_stat_all.txt' % (analysis) 
6790                      else: 
6791                          file_name = '%s_stat_sel.txt' % (analysis) 
6792                      path = RDR.results_dir 
6793                      data = extract_data(file=file_name, dir=path) 
6794   
6795                      # Loop over the lines. 
6796                      for i, data_i in enumerate(data): 
6797                          print(i, data_i) 
6798   
6799   
6800   
6801 -    def test_r1rho_kjaergaard_auto(self): 
6802          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
6803   
6804          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6805   
6806          This uses the automatic analysis. 
6807   
6808          """ 
6809   
6810          # Cluster residues 
6811          cluster_ids = [ 
6812          ":13@N", 
6813          ":15@N", 
6814          ":16@N", 
6815          ":25@N", 
6816          ":26@N", 
6817          ":28@N", 
6818          ":39@N", 
6819          ":40@N", 
6820          ":41@N", 
6821          ":43@N", 
6822          ":44@N", 
6823          ":45@N", 
6824          ":49@N", 
6825          ":52@N", 
6826          ":53@N"] 
6827   
6828          # Load the data. 
6829          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
6830   
6831          # Test some of the sequence. 
6832          self.assertEqual(len(cdp.mol), 1) 
6833          self.assertEqual(cdp.mol[0].name, None) 
6834          self.assertEqual(len(cdp.mol[0].res), 48) 
6835   
6836          # Test the chemical shift data. 
6837          cs = [122.223, 122.162, 114.250, 125.852, 118.626, 117.449, 119.999, 122.610, 118.602, 118.291, 115.393, 
6838          121.288, 117.448, 116.378, 116.316, 117.263, 122.211, 118.748, 118.103, 119.421, 119.317, 119.386, 117.279, 
6839          122.103, 120.038, 116.698, 111.811, 118.639, 118.285, 121.318, 117.770, 119.948, 119.759, 118.314, 118.160, 
6840          121.442, 118.714, 113.080, 125.706, 119.183, 120.966, 122.361, 126.675, 117.069, 120.875, 109.372, 119.811, 126.048] 
6841   
6842          i = 0 
6843          for spin, spin_id in spin_loop(return_id=True): 
6844              # Check the chemical shift. 
6845              self.assertEqual(spin.chemical_shift, cs[i]) 
6846   
6847              # Increment the index. 
6848              i += 1 
6849   
6850          # Initialize counter 
6851          i = 0 
6852          j = 0 
6853          # Count instances of select/deselect 
6854          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
6855              if curspin.select == True: 
6856                  i += 1 
6857              if curspin.select == False: 
6858                  j += 1 
6859   
6860          # Test number of selected/deselected spins. 
6861          self.assertEqual(i, len(cluster_ids)) 
6862          self.assertEqual(j, 48-len(cluster_ids)) 
6863   
6864          # Check the initial setup. 
6865          self.assertEqual(cdp.mol[0].res[7].num, 13) 
6866          self.assertEqual(cdp.mol[0].res[7].spin[0].kex, ds.guess[':13@N'][6]) 
6867          self.assertEqual(cdp.mol[0].res[7].spin[0].ri_data['R1'], ds.ref[':13@N'][2]) 
6868   
6869          self.assertEqual(cdp.mol[0].res[9].num, 15) 
6870          self.assertEqual(cdp.mol[0].res[9].spin[0].kex, ds.guess[':15@N'][6]) 
6871          self.assertEqual(cdp.mol[0].res[9].spin[0].ri_data['R1'], ds.ref[':15@N'][2]) 
6872   
6873          self.assertEqual(cdp.mol[0].res[10].num, 16) 
6874          self.assertEqual(cdp.mol[0].res[10].spin[0].kex, ds.guess[':16@N'][6]) 
6875          self.assert_(hasattr(cdp.mol[0].res[10].spin[0], 'ri_data')) 
6876   
6877          self.assertEqual(cdp.mol[0].res[16].num, 25) 
6878          self.assertEqual(cdp.mol[0].res[16].spin[0].kex, ds.guess[':25@N'][6]) 
6879          self.assert_(hasattr(cdp.mol[0].res[16].spin[0], 'ri_data')) 
6880   
6881          self.assertEqual(cdp.mol[0].res[17].num, 26) 
6882          self.assertEqual(cdp.mol[0].res[17].spin[0].kex, ds.guess[':26@N'][6]) 
6883          self.assert_(hasattr(cdp.mol[0].res[17].spin[0], 'ri_data')) 
6884   
6885          self.assertEqual(cdp.mol[0].res[19].num, 28) 
6886          self.assertEqual(cdp.mol[0].res[19].spin[0].kex, ds.guess[':28@N'][6]) 
6887          self.assert_(hasattr(cdp.mol[0].res[19].spin[0], 'ri_data')) 
6888   
6889          self.assertEqual(cdp.mol[0].res[29].num, 39) 
6890          self.assertEqual(cdp.mol[0].res[29].spin[0].kex, ds.guess[':39@N'][6]) 
6891          self.assert_(hasattr(cdp.mol[0].res[29].spin[0], 'ri_data')) 
6892   
6893          self.assertEqual(cdp.mol[0].res[30].num, 40) 
6894          self.assertEqual(cdp.mol[0].res[30].spin[0].kex, ds.guess[':40@N'][6]) 
6895          self.assert_(hasattr(cdp.mol[0].res[30].spin[0], 'ri_data')) 
6896   
6897          self.assertEqual(cdp.mol[0].res[31].num, 41) 
6898          self.assertEqual(cdp.mol[0].res[31].spin[0].kex, ds.guess[':41@N'][6]) 
6899          self.assert_(hasattr(cdp.mol[0].res[31].spin[0], 'ri_data')) 
6900   
6901          self.assertEqual(cdp.mol[0].res[33].num, 43) 
6902          self.assertEqual(cdp.mol[0].res[33].spin[0].kex, ds.guess[':43@N'][6]) 
6903          self.assert_(hasattr(cdp.mol[0].res[33].spin[0], 'ri_data')) 
6904   
6905          self.assertEqual(cdp.mol[0].res[34].num, 44) 
6906          self.assertEqual(cdp.mol[0].res[34].spin[0].kex, ds.guess[':44@N'][6]) 
6907          self.assert_(hasattr(cdp.mol[0].res[34].spin[0], 'ri_data')) 
6908   
6909          self.assertEqual(cdp.mol[0].res[35].num, 45) 
6910          self.assertEqual(cdp.mol[0].res[35].spin[0].kex, ds.guess[':45@N'][6]) 
6911          self.assert_(hasattr(cdp.mol[0].res[35].spin[0], 'ri_data')) 
6912   
6913          self.assertEqual(cdp.mol[0].res[38].num, 49) 
6914          self.assertEqual(cdp.mol[0].res[38].spin[0].kex, ds.guess[':49@N'][6]) 
6915          self.assert_(hasattr(cdp.mol[0].res[38].spin[0], 'ri_data')) 
6916   
6917          self.assertEqual(cdp.mol[0].res[41].num, 52) 
6918          self.assertEqual(cdp.mol[0].res[41].spin[0].kex, ds.guess[':52@N'][6]) 
6919          self.assert_(hasattr(cdp.mol[0].res[41].spin[0], 'ri_data')) 
6920   
6921          self.assertEqual(cdp.mol[0].res[42].num, 53) 
6922          self.assertEqual(cdp.mol[0].res[42].spin[0].kex, ds.guess[':53@N'][6]) 
6923          self.assert_(hasattr(cdp.mol[0].res[42].spin[0], 'ri_data')) 
6924   
6925          # The dispersion models. 
6926          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
6927   
6928          # The grid search size (the number of increments per dimension). 
6929          GRID_INC = 4 
6930   
6931          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6932          MC_NUM = 3 
6933   
6934          # Model selection technique. 
6935          MODSEL = 'AIC' 
6936   
6937          # Execute the auto-analysis (fast). 
6938          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6939          OPT_FUNC_TOL = 1e-1 
6940          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6941          OPT_MAX_ITERATIONS = 1000 
6942          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6943   
6944          result_dir_name = ds.tmpdir 
6945   
6946          # Make all spins free 
6947          for curspin in cluster_ids: 
6948              self.interpreter.relax_disp.cluster('free spins', curspin) 
6949              # Shut them down 
6950              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
6951   
6952          # Select only a subset of spins for global fitting 
6953          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
6954          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
6955   
6956          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
6957          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
6958   
6959          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
6960          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
6961   
6962          # Run the analysis. 
6963          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
6964   
6965          # Check the kex value of residue 52 
6966          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
6967   
6968          # Print results for each model. 
6969          print("\n\n################") 
6970          print("Printing results") 
6971          print("################\n") 
6972          for model in MODELS: 
6973              # Skip R2eff model. 
6974              if model == MODEL_R2EFF: 
6975                  continue 
6976   
6977              # Switch to pipe. 
6978              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
6979              print("\nModel: %s" % (model)) 
6980   
6981              # Loop over the spins. 
6982              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
6983                  # Generate spin string. 
6984                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
6985   
6986                  # Loop over the parameters. 
6987                  print("Optimised parameters for spin: %s" % (spin_string)) 
6988                  for param in cur_spin.params + ['chi2']: 
6989                      # Get the value. 
6990                      if param in ['r1', 'r2']: 
6991                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
6992                              # Generate the R20 key. 
6993                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
6994   
6995                              # Get the value. 
6996                              value = getattr(cur_spin, param)[r20_key] 
6997   
6998                              # Print value. 
6999                              print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
7000   
7001                      # For all other parameters. 
7002                      else: 
7003                          # Get the value. 
7004                          value = getattr(cur_spin, param) 
7005   
7006                          # Print value. 
7007                          print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
7008   
7009          # Print the final pipe. 
7010          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % ('final')) 
7011          print("\nFinal pipe") 
7012   
7013   
7014 -    def test_r1rho_kjaergaard_auto_check_graphs(self): 
7015          """Check of plot_disp_curves() function, after optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'R2eff' model. 
7016   
7017          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
7018   
7019          This uses the automatic analysis. 
7020   
7021          """ 
7022   
7023          # Cluster residues 
7024          cluster_ids = [ 
7025          ":52@N"] 
7026   
7027          # Load the data. 
7028          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
7029   
7030          # The dispersion models. 
7031          MODELS = [MODEL_R2EFF] 
7032   
7033          # The grid search size (the number of increments per dimension). 
7034          GRID_INC = 4 
7035   
7036          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7037          MC_NUM = 3 
7038   
7039          # Model selection technique. 
7040          MODSEL = 'AIC' 
7041   
7042          # Execute the auto-analysis (fast). 
7043          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7044          OPT_FUNC_TOL = 1e-1 
7045          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7046          OPT_MAX_ITERATIONS = 1000 
7047          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7048   
7049          result_dir_name = ds.tmpdir 
7050   
7051          # Make all spins free 
7052          for curspin in cluster_ids: 
7053              self.interpreter.relax_disp.cluster('free spins', curspin) 
7054              # Shut them down 
7055              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7056   
7057          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7058   
7059          # Run the analysis. 
7060          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
7061   
7062          # Check the graphs produced. 
7063          graph_comb = [ 
7064          [Y_AXIS_R2_EFF, X_AXIS_DISP, INTERPOLATE_DISP], 
7065          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_DISP], 
7066          [Y_AXIS_R2_R1RHO, X_AXIS_W_EFF, INTERPOLATE_DISP], 
7067          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_OFFSET] 
7068          ] 
7069   
7070          # Define expected folder names. 
7071          result_folders = MODELS 
7072   
7073          # Assign spin_id. 
7074          spin_id = ':52@N' 
7075   
7076          # Loop over result folders. 
7077          for result_folder in result_folders: 
7078              # Skip the model R2eff, which does not produce graphs. 
7079              if result_folder == MODEL_R2EFF: 
7080                  continue 
7081   
7082              # Loop over graphs. 
7083              for y_axis, x_axis, interpolate in graph_comb: 
7084                  # Determine file name: 
7085                  file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7086   
7087                  # Make the file name. 
7088                  file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7089   
7090                  # Get the file path. 
7091                  file_path = get_file_path(file_name, result_dir_name+sep+result_folder) 
7092   
7093                  print("Testing file access to graph: %s"%file_path) 
7094                  self.assert_(access(file_path, F_OK)) 
7095   
7096          # Start testing all possible combinations of graphs. 
7097          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
7098          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
7099          interpolate_types = [INTERPOLATE_DISP, INTERPOLATE_OFFSET] 
7100   
7101          result_dir_name = ds.tmpdir 
7102   
7103          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
7104          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep+'check_graphs' 
7105   
7106          for result_folder in result_folders: 
7107              # Skip the model R2eff, which does not produce graphs. 
7108              if result_folder == MODEL_R2EFF: 
7109                  continue 
7110   
7111              for y_axis in y_axis_types: 
7112                  for x_axis in x_axis_types: 
7113                      for interpolate in interpolate_types: 
7114                          # Determine file name: 
7115                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7116   
7117                          # Make the file name. 
7118                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7119   
7120                          # Write the curves. 
7121                          dir = result_dir_name+sep+result_folder 
7122                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
7123                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
7124   
7125                          # Get the file path. 
7126                          file_path = get_file_path(file_name, dir) 
7127   
7128                          # Test the plot file exists. 
7129                          print("Testing file access to graph: %s"%file_path) 
7130                          self.assert_(access(file_path, F_OK)) 
7131   
7132                          # Now open, and compare content, line by line. 
7133                          file_prod = open(file_path) 
7134                          lines_prod = file_prod.readlines() 
7135                          file_prod.close() 
7136   
7137                          # Define file to compare against. 
7138                          dir_comp = data_path+sep+result_folder 
7139                          file_path_comp = get_file_path(file_name, dir_comp) 
7140                          file_comp = open(file_path_comp) 
7141                          lines_comp = file_comp.readlines() 
7142                          file_comp.close() 
7143   
7144                          # Assert number of lines is equal. 
7145                          self.assertEqual(len(lines_prod), len(lines_comp)) 
7146                          for j in range(len(lines_prod)): 
7147                              # Make the string test 
7148                              first_char = lines_prod[j][0] 
7149                              if first_char in ["@", "&"]: 
7150                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
7151                              else: 
7152                                  # Split string in x, y, error. 
7153                                  # The error would change per run. 
7154                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
7155                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
7156                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
7157                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
7158   
7159   
7160 -    def test_r1rho_kjaergaard_missing_r1(self): 
7161          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
7162   
7163          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
7164   
7165          This uses the automatic analysis, with missing loading R1. 
7166   
7167          """ 
7168   
7169          # Cluster residues 
7170          cluster_ids = [ 
7171          ":13@N", 
7172          ":15@N", 
7173          ":16@N", 
7174          ":25@N", 
7175          ":26@N", 
7176          ":28@N", 
7177          ":39@N", 
7178          ":40@N", 
7179          ":41@N", 
7180          ":43@N", 
7181          ":44@N", 
7182          ":45@N", 
7183          ":49@N", 
7184          ":52@N", 
7185          ":53@N"] 
7186   
7187          # Load the data. 
7188          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
7189   
7190          # The dispersion models. 
7191          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
7192   
7193          # The grid search size (the number of increments per dimension). 
7194          GRID_INC = None 
7195   
7196          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7197          MC_NUM = 3 
7198   
7199          # Model selection technique. 
7200          MODSEL = 'AIC' 
7201   
7202          # Execute the auto-analysis (fast). 
7203          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7204          OPT_FUNC_TOL = 1e-25 
7205          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7206          OPT_MAX_ITERATIONS = 10000000 
7207          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7208   
7209          result_dir_name = ds.tmpdir 
7210   
7211          # Make all spins free 
7212          for curspin in cluster_ids: 
7213              self.interpreter.relax_disp.cluster('free spins', curspin) 
7214              # Shut them down 
7215              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7216   
7217          # Select only a subset of spins for global fitting 
7218          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
7219          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
7220   
7221          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
7222          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
7223   
7224          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7225          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
7226   
7227          # Point to directory with R2eff values, with 2000 MC simulations. 
7228          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000" 
7229   
7230          r1_fit = True 
7231   
7232          # Run the analysis. 
7233          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, pre_run_dir=prev_data_path, r1_fit=r1_fit) 
7234   
7235          # Verify the data. 
7236          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='MC2000') 
7237   
7238   
7239 -    def test_r2eff_read(self): 
7240          """Test the operation of the relax_disp.r2eff_read user function.""" 
7241   
7242          # The path to the data files. 
7243          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'800_MHz' 
7244   
7245          # Read the sequence data. 
7246          self.interpreter.sequence.read(file='66.667.in', dir=data_path, res_num_col=1) 
7247   
7248          # The ID. 
7249          id = 'test' 
7250   
7251          # Set up the metadata. 
7252          self.interpreter.spectrometer.frequency(id=id, frq=800e6) 
7253          self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7254   
7255          # Try reading the file. 
7256          self.interpreter.relax_disp.r2eff_read(id=id, file='66.667.in', dir=data_path, disp_frq=66.667, res_num_col=1, data_col=2, error_col=3) 
7257   
7258          # Check the global data. 
7259          data = [ 
7260              ['cpmg_frqs', {'test': 66.667}], 
7261              ['cpmg_frqs_list', [66.667]], 
7262              ['dispersion_points', 1], 
7263              ['exp_type', {'test': 'SQ CPMG'}], 
7264              ['exp_type_list', ['SQ CPMG']], 
7265              ['spectrometer_frq', {'test': 800000000.0}], 
7266              ['spectrometer_frq_count', 1], 
7267              ['spectrometer_frq_list', [800000000.0]], 
7268              ['spectrum_ids', ['test']] 
7269          ] 
7270          for name, value in data: 
7271              # Does it exist? 
7272              self.assert_(hasattr(cdp, name)) 
7273   
7274              # Check the object. 
7275              obj = getattr(cdp, name) 
7276              self.assertEqual(obj, value) 
7277   
7278          # Check the spin data. 
7279          data = [ 
7280              [1,       2.3035747e+04, 8.5467725e+01], 
7281              [2,       9.9629762e+04, 2.8322033e+02], 
7282              [3,       9.5663137e+04, 2.8632929e+02], 
7283              [4,       1.7089893e+05, 3.1089428e+02], 
7284              [5,       4.7323876e+04, 1.0084269e+02], 
7285              [6,       2.0199122e+04, 1.0135220e+02], 
7286              [7,       1.6655488e+05, 3.1609061e+02], 
7287              [8,       9.0061074e+04, 1.9176585e+02], 
7288              [10,      8.4726204e+04, 2.8898155e+02], 
7289              [11,      1.5050233e+05, 4.3138029e+02], 
7290              [12,      9.2998531e+04, 3.0440191e+02], 
7291              [13,      1.6343507e+05, 3.3144097e+02], 
7292              [14,      1.0137301e+05, 3.7314642e+02], 
7293              [15,      8.3407837e+04, 1.6546473e+02], 
7294              [16,      1.3819126e+05, 3.3388517e+02], 
7295              [17,      1.1010490e+05, 3.5639222e+02], 
7296              [18,      9.4324035e+04, 3.2343585e+02], 
7297              [19,      1.1135179e+05, 3.0706671e+02], 
7298              [20,      7.6339410e+04, 1.7377460e+02], 
7299              [21,      6.2008453e+04, 1.7327150e+02], 
7300              [22,      1.0590404e+05, 2.4814635e+02], 
7301              [23,      1.0630198e+05, 2.3601100e+02], 
7302              [24,      7.2996320e+04, 1.4952465e+02], 
7303              [25,      9.5486742e+04, 2.7080766e+02], 
7304              [26,      5.8067989e+04, 1.6820462e+02], 
7305              [27,     -1.7168510e+04, 2.2519560e+02], 
7306              [28,      1.6891473e+05, 2.3497525e+02], 
7307              [29,      9.4038555e+04, 2.0357593e+02], 
7308              [30,      2.1386951e+04, 2.2153532e+02], 
7309              [31,      9.3982899e+04, 2.0937056e+02], 
7310              [32,      8.6097484e+04, 2.3868467e+02], 
7311              [33,      1.0194337e+05, 2.7370704e+02], 
7312              [34,      8.5683111e+04, 2.0838076e+02], 
7313              [35,      8.6985768e+04, 2.0889310e+02], 
7314              [36,      8.6011237e+04, 1.7498390e+02], 
7315              [37,      1.0984097e+05, 2.7622998e+02], 
7316              [38,      8.7017879e+04, 2.6547994e+02], 
7317              [39,      9.1682649e+04, 5.2777676e+02], 
7318              [40,      7.6370440e+04, 1.9873214e+02], 
7319              [41,      9.1393531e+04, 2.4483824e+02], 
7320              [42,      1.1017111e+05, 2.8020699e+02], 
7321              [43,      9.4552366e+04, 3.4394150e+02], 
7322              [44,      1.2858281e+05, 6.8449252e+02], 
7323              [45,      7.4583525e+04, 1.9544210e+02], 
7324              [46,      9.2087490e+04, 2.0491066e+02], 
7325              [47,      9.7507255e+04, 2.5162839e+02], 
7326              [48,      1.0033842e+05, 2.7566430e+02], 
7327              [49,      1.3048305e+05, 2.6797466e+02], 
7328              [50,      1.0546796e+05, 1.9304384e+02], 
7329              [51,      9.3099697e+04, 2.0773311e+02], 
7330              [52,      4.6863758e+04, 1.3169068e+02], 
7331              [53,      6.1055806e+04, 1.5448477e+02], 
7332              [55,      6.8629994e+04, 1.6868673e+02], 
7333              [56,      1.1005552e+05, 2.1940465e+02], 
7334              [57,      1.0572760e+05, 1.9768486e+02], 
7335              [58,      1.1176950e+05, 3.0009610e+02], 
7336              [59,      9.8758603e+04, 3.3803895e+02], 
7337              [60,      9.9517201e+04, 3.5137994e+02], 
7338              [61,      5.4357946e+04, 2.5896579e+02], 
7339              [62,      1.0899978e+05, 2.8720371e+02], 
7340              [63,      8.4549759e+04, 4.1401837e+02], 
7341              [64,      5.5014550e+04, 2.1135781e+02], 
7342              [65,      8.0569666e+04, 2.3249709e+02], 
7343              [66,      1.2936610e+05, 3.5218725e+02], 
7344              [67,      3.6438010e+04, 8.7924003e+01], 
7345              [70,      3.8763157e+04, 1.3325040e+02], 
7346              [71,      8.5711411e+04, 2.9316183e+02], 
7347              [72,      3.3211541e+04, 1.2182123e+02], 
7348              [73,      3.2070576e+04, 1.2305430e+02] 
7349          ] 
7350          for res_num, value, error in data: 
7351              # Get the spin. 
7352              spin = return_spin(spin_id=":%s"%res_num) 
7353   
7354              # Check the values. 
7355              self.assertEqual(spin.r2eff['sq_cpmg_800.00000000_0.000_66.667'], value) 
7356              self.assertEqual(spin.r2eff_err['sq_cpmg_800.00000000_0.000_66.667'], error) 
7357   
7358   
7359 -    def test_r2eff_read_spin(self): 
7360          """Test the operation of the relax_disp.r2eff_read_spin user function.""" 
7361   
7362          # The path to the data files. 
7363          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
7364   
7365          # Generate the sequence. 
7366          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
7367          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
7368          self.interpreter.spin.isotope('1H', spin_id='@H') 
7369          self.interpreter.spin.isotope('15N', spin_id='@N') 
7370   
7371          # Build the experiment IDs. 
7372          H_disp_points = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
7373          N_disp_points = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
7374          ids = [] 
7375          for value in H_disp_points: 
7376              ids.append('1H_CPMG_%s' % value) 
7377          for value in N_disp_points: 
7378              ids.append('15N_CPMG_%s' % value) 
7379          print("\n\nThe experiment IDs are %s." % ids) 
7380   
7381          # Set up the metadata for the experiments. 
7382          for id in ids: 
7383              self.interpreter.spectrometer.frequency(id=id, frq=500e6) 
7384              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7385          for value in H_disp_points: 
7386              self.interpreter.relax_disp.cpmg_setup(spectrum_id='1H_CPMG_%s' % value, cpmg_frq=value) 
7387          for value in N_disp_points: 
7388              self.interpreter.relax_disp.cpmg_setup(spectrum_id='15N_CPMG_%s' % value, cpmg_frq=value) 
7389   
7390          # Loop over the experiments. 
7391          for id, file, spin_id in [['1H_CPMG', 'hs_500.res', ':9@H'], ['15N_CPMG', 'ns_500.res', ':9@N']]: 
7392              # Try reading the file. 
7393              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
7394   
7395          # Check the global data. 
7396          data = [ 
7397              ['cpmg_frqs', {'1H_CPMG_667.0': 667.0, '1H_CPMG_1067.0': 1067.0, '15N_CPMG_350.0': 350.0, '1H_CPMG_933.0': 933.0, '15N_CPMG_50.0': 50.0, '15N_CPMG_100.0': 100.0, '1H_CPMG_400.0': 400.0, '1H_CPMG_533.0': 533.0, '1H_CPMG_800.0': 800.0, '15N_CPMG_900.0': 900.0, '15N_CPMG_150.0': 150.0, '15N_CPMG_800.0': 800.0, '1H_CPMG_267.0': 267.0, '1H_CPMG_2667.0': 2667.0, '15N_CPMG_300.0': 300.0, '1H_CPMG_133.0': 133.0, '15N_CPMG_700.0': 700.0, '1H_CPMG_67.0': 67.0, '15N_CPMG_400.0': 400.0, '15N_CPMG_250.0': 250.0, '1H_CPMG_2133.0': 2133.0, '1H_CPMG_1600.0': 1600.0, '15N_CPMG_200.0': 200.0, '15N_CPMG_1000.0': 1000.0, '15N_CPMG_500.0': 500.0, '15N_CPMG_600.0': 600.0}], 
7398              ['cpmg_frqs_list', [50.0, 67.0, 100.0, 133.0, 150.0, 200.0, 250.0, 267.0, 300.0, 350.0, 400.0, 500.0, 533.0, 600.0, 667.0, 700.0, 800.0, 900.0, 933.0, 1000.0, 1067.0, 1600.0, 2133.0, 2667.0]], 
7399              ['dispersion_points', 24], 
7400              ['exp_type', {'1H_CPMG_667.0': 'SQ CPMG', '1H_CPMG_1067.0': 'SQ CPMG', '15N_CPMG_350.0': 'SQ CPMG', '1H_CPMG_933.0': 'SQ CPMG', '15N_CPMG_50.0': 'SQ CPMG', '15N_CPMG_100.0': 'SQ CPMG', '1H_CPMG_400.0': 'SQ CPMG', '1H_CPMG_533.0': 'SQ CPMG', '1H_CPMG_800.0': 'SQ CPMG', '15N_CPMG_900.0': 'SQ CPMG', '15N_CPMG_150.0': 'SQ CPMG', '15N_CPMG_800.0': 'SQ CPMG', '1H_CPMG_267.0': 'SQ CPMG', '1H_CPMG_2667.0': 'SQ CPMG', '15N_CPMG_300.0': 'SQ CPMG', '1H_CPMG_133.0': 'SQ CPMG', '15N_CPMG_700.0': 'SQ CPMG', '1H_CPMG_67.0': 'SQ CPMG', '15N_CPMG_400.0': 'SQ CPMG', '15N_CPMG_250.0': 'SQ CPMG', '1H_CPMG_2133.0': 'SQ CPMG', '1H_CPMG_1600.0': 'SQ CPMG', '15N_CPMG_200.0': 'SQ CPMG', '15N_CPMG_1000.0': 'SQ CPMG', '15N_CPMG_500.0': 'SQ CPMG', '15N_CPMG_600.0': 'SQ CPMG'}], 
7401              ['exp_type_list', ['SQ CPMG']], 
7402              ['spectrometer_frq', {'1H_CPMG_667.0': 500000000.0, '1H_CPMG_1067.0': 500000000.0, '15N_CPMG_350.0': 500000000.0, '1H_CPMG_933.0': 500000000.0, '15N_CPMG_50.0': 500000000.0, '15N_CPMG_100.0': 500000000.0, '1H_CPMG_400.0': 500000000.0, '1H_CPMG_533.0': 500000000.0, '1H_CPMG_800.0': 500000000.0, '15N_CPMG_900.0': 500000000.0, '15N_CPMG_150.0': 500000000.0, '15N_CPMG_800.0': 500000000.0, '1H_CPMG_267.0': 500000000.0, '1H_CPMG_2667.0': 500000000.0, '15N_CPMG_300.0': 500000000.0, '1H_CPMG_133.0': 500000000.0, '15N_CPMG_700.0': 500000000.0, '1H_CPMG_67.0': 500000000.0, '15N_CPMG_400.0': 500000000.0, '15N_CPMG_250.0': 500000000.0, '1H_CPMG_2133.0': 500000000.0, '1H_CPMG_1600.0': 500000000.0, '15N_CPMG_200.0': 500000000.0, '15N_CPMG_1000.0': 500000000.0, '15N_CPMG_500.0': 500000000.0, '15N_CPMG_600.0': 500000000.0}], 
7403              ['spectrometer_frq_count', 1], 
7404              ['spectrometer_frq_list', [500000000.0]], 
7405              ['spectrum_ids', ['1H_CPMG_67.0', '1H_CPMG_133.0', '1H_CPMG_267.0', '1H_CPMG_400.0', '1H_CPMG_533.0', '1H_CPMG_667.0', '1H_CPMG_800.0', '1H_CPMG_933.0', '1H_CPMG_1067.0', '1H_CPMG_1600.0', '1H_CPMG_2133.0', '1H_CPMG_2667.0', '15N_CPMG_50.0', '15N_CPMG_100.0', '15N_CPMG_150.0', '15N_CPMG_200.0', '15N_CPMG_250.0', '15N_CPMG_300.0', '15N_CPMG_350.0', '15N_CPMG_400.0', '15N_CPMG_500.0', '15N_CPMG_600.0', '15N_CPMG_700.0', '15N_CPMG_800.0', '15N_CPMG_900.0', '15N_CPMG_1000.0']] 
7406          ] 
7407          for name, value in data: 
7408              # Does it exist? 
7409              self.assert_(hasattr(cdp, name)) 
7410   
7411              # Check the object. 
7412              obj = getattr(cdp, name) 
7413              if not isinstance(data, dict): 
7414                  self.assertEqual(obj, value) 
7415   
7416              # Check the global dictionary data. 
7417              else: 
7418                  for id in ids: 
7419                      self.assertEqual(obj[id], value[id]) 
7420   
7421          # Check the spin data. 
7422          h_data = [ 
7423              [  67.0,  21.47924,   0.42958], 
7424              [ 133.0,  16.73898,   0.33478], 
7425              [ 267.0,   9.97357,   0.19947], 
7426              [ 400.0,   8.23877,   0.24737], 
7427              [ 533.0,   7.59290,   0.24263], 
7428              [ 667.0,   7.45843,   0.24165], 
7429              [ 800.0,   7.11222,   0.23915], 
7430              [ 933.0,   7.40880,   0.24129], 
7431              [1067.0,   6.55191,   0.16629], 
7432              [1600.0,   6.72177,   0.23637], 
7433              [2133.0,   7.09629,   0.23904], 
7434              [2667.0,   7.14675,   0.23940] 
7435          ] 
7436          for disp_point, value, error in h_data: 
7437              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7438              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
7439              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
7440          n_data = [ 
7441              [  50.0,  27.15767,   0.54315], 
7442              [ 100.0,  26.55781,   0.53116], 
7443              [ 150.0,  24.73462,   0.49469], 
7444              [ 200.0,  20.98617,   0.41972], 
7445              [ 250.0,  17.82442,   0.35649], 
7446              [ 300.0,  15.55352,   0.31107], 
7447              [ 350.0,  13.78958,   0.27579], 
7448              [ 400.0,  12.48334,   0.24967], 
7449              [ 500.0,  11.55724,   0.23114], 
7450              [ 600.0,  10.53874,   0.21077], 
7451              [ 700.0,  10.07395,   0.20148], 
7452              [ 800.0,   9.62952,   0.19259], 
7453              [ 900.0,   9.49994,   0.19000], 
7454              [1000.0,   8.71350,   0.17427] 
7455          ] 
7456          for disp_point, value, error in n_data: 
7457              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7458              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff[id], value) 
7459              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff_err[id], error) 
7460   
7461   
7462 -    def test_r2eff_fit_fixed_time(self): 
7463          """Test the relaxation dispersion 'R2eff' model for fixed time data in the auto-analysis.""" 
7464   
7465          # Execute the script. 
7466          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r2eff_calc.py') 
7467   
7468   
7469 -    def test_read_r2eff(self): 
7470          """Test the reading of a file containing r2eff values.""" 
7471   
7472          # Create the sequence data, and name the spins. 
7473          self.interpreter.residue.create(1, 'Gly') 
7474          self.interpreter.residue.create(2, 'Gly') 
7475          self.interpreter.residue.create(3, 'Gly') 
7476   
7477          # Read the file. 
7478          self.interpreter.relax_data.read(ri_id='R2eff.600', ri_type='R2eff', frq=600*1e6, file='r2eff.out', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r2eff', res_num_col=1, res_name_col=2, data_col=3, error_col=4) 
7479   
7480          # Test the data. 
7481          self.assertEqual(cdp.mol[0].res[0].spin[0].ri_data['R2eff.600'], 15.000) 
7482          self.assertEqual(cdp.mol[0].res[1].spin[0].ri_data['R2eff.600'], 4.2003) 
7483          self.assertEqual(cdp.mol[0].res[2].spin[0].ri_data['R2eff.600'], 7.2385) 
7484   
7485   
7486 -    def test_r20_from_min_r2eff_cpmg(self): 
7487          """Test speeding up grid search. Support requst sr #3151 U{https://gna.org/support/index.php?3151}. 
7488   
7489          User function to set the R20 parameters in the default grid search using the minimum R2eff value. 
7490   
7491          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7492          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7493   
7494          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7495          Data is for experiment at 25 degree Celcius. 
7496          """ 
7497   
7498          # Base data setup. 
7499          pipe_name = 'base pipe' 
7500          pipe_type = 'relax_disp' 
7501          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7502          select_spin_index = list(range(0, 1)) 
7503          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7504   
7505          # Generate r20 key. 
7506          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7507          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7508   
7509          ## Now prepare for MODEL calculation. 
7510          MODEL = "CR72" 
7511   
7512          # Change pipe. 
7513          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7514          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7515          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7516   
7517          # Then select model. 
7518          self.interpreter.relax_disp.select_model(model=MODEL) 
7519   
7520          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7521          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7522   
7523          # Test result, for normal run. 
7524          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7525              # Get the spin_params. 
7526              spin_params = spin.params 
7527   
7528              # Defined fixed values for testing. 
7529              if spin_id == ":10@N": 
7530                  self.assertEqual(spin.r2[r20_key_600], 20.282732526087106) 
7531                  self.assertEqual(spin.r2[r20_key_500], 18.475299724356649) 
7532   
7533              # Print out. 
7534              print("r2_600=%2.2f r2_500=%2.2f spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin_id, resi, resn)) 
7535   
7536              # Testing the r2 values for the different fields are not the same. 
7537              self.assert_(spin.r2[r20_key_600] != spin.r2[r20_key_500]) 
7538   
7539              # Test values are larger than 0. 
7540              self.assert_(spin.r2[r20_key_600] > 0.0) 
7541              self.assert_(spin.r2[r20_key_500] > 0.0) 
7542   
7543              # Loop over the experiment settings. 
7544              r2eff_600 = [] 
7545              r2eff_500 = [] 
7546              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
7547                  # Create the data key. 
7548                  data_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
7549   
7550                  # Extract the r2 eff data. 
7551                  r2eff = spin.r2eff[data_key] 
7552                  if frq == 599.8908617*1E6: 
7553                      r2eff_600.append(r2eff) 
7554                  elif frq == 499.862139*1E6: 
7555                      r2eff_500.append(r2eff) 
7556   
7557              # Sort values. 
7558              r2eff_600.sort() 
7559              r2eff_500.sort() 
7560   
7561              # Test values again. 
7562              print("For r20 600MHz min r2eff=%3.3f."%(min(r2eff_600))) 
7563              print(r2eff_600) 
7564              self.assertEqual(spin.r2[r20_key_600], min(r2eff_600)) 
7565              print("") 
7566   
7567              print("For r20 500MHz min r2eff=%3.3f."%(min(r2eff_500))) 
7568              print(r2eff_500) 
7569              self.assertEqual(spin.r2[r20_key_500], min(r2eff_500)) 
7570              print("") 
7571   
7572          print("###########################################") 
7573          print("Trying GRID SEARCH for minimum R2eff values") 
7574   
7575          ### Test just the Grid search. 
7576          GRID_INC = 5 
7577   
7578          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7579   
7580          ### Then test the value.set function. 
7581          # Change pipe. 
7582          pipe_name_MODEL = "%s_%s_2"%(pipe_name, MODEL) 
7583          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7584          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7585   
7586          # Then select model. 
7587          self.interpreter.relax_disp.select_model(model=MODEL) 
7588   
7589          # Then set the standard parameter values. 
7590          for param in spin_params: 
7591              print("Setting standard parameter for param: %s"%param) 
7592              self.interpreter.value.set(param=param, index=None) 
7593   
7594          # Test result, for normal run. 
7595          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7596              # Print out. 
7597              print("r2_600=%2.2f r2_500=%2.2f pA=%2.2f, dw=%2.2f, kex=%2.2f, spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin.pA, spin.dw, spin.kex, spin_id, resi, resn)) 
7598   
7599              # Testing the r2 values. 
7600              self.assertEqual(spin.r2[r20_key_600], 10.00) 
7601              self.assertEqual(spin.r2[r20_key_500], 10.00) 
7602              self.assertEqual(spin.pA, 0.9) 
7603              self.assertEqual(spin.dw, 1.0) 
7604              self.assertEqual(spin.kex, 1000.0) 
7605   
7606          print("###########################################") 
7607          print("Trying GRID SEARCH for standard R2eff values") 
7608   
7609          ### Test just the Grid search. 
7610          GRID_INC = 5 
7611   
7612          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7613   
7614          ### Run auto_analysis. 
7615          # The grid search size (the number of increments per dimension). 
7616          GRID_INC = 5 
7617   
7618          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7619          MC_NUM = 3 
7620   
7621          # Model selection technique. 
7622          MODSEL = 'AIC' 
7623   
7624          # Execute the auto-analysis (fast). 
7625          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7626          OPT_FUNC_TOL = 1e-1 
7627          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7628          OPT_MAX_ITERATIONS = 1000 
7629          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7630   
7631          # Run the analysis. 
7632          relax_disp.Relax_disp(pipe_name=pipe_name_r2eff, results_dir=ds.tmpdir, models=[MODEL], grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, set_grid_r20=True) 
7633   
7634   
7635 -    def test_show_apod_extract(self): 
7636          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7637   
7638          # The path to the data files. 
7639          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7640   
7641          # Define file name. 
7642          file_name = '128_0_FT.ft2' 
7643   
7644          # Call function. 
7645          get_output = show_apod_extract(file_name=file_name, dir=data_path) 
7646   
7647          # Define how output should look like. 
7648          # The output from showApod differs slightly according to NMRPipe version. But 'Noise Std Dev' is the same. 
7649          # Dont test lines which can differ. 
7650          show_apod_ver = [ 
7651              'REMARK Effect of Processing on Peak Parameters and Noise for %s'%(data_path+sep+file_name), 
7652              'REMARK Automated Noise Std Dev in Processed Data: 8583.41', 
7653              'REMARK Noise Std Dev Before Processing H1 and N15: 60.6558', 
7654              '', 
7655              'VARS   AXIS LABEL  TSIZE FSIZE LW_ADJ LW_FINAL HI_FACTOR VOL_FACTOR SIGMA_FACTOR', 
7656              'FORMAT %s   %-8s   %4d   %4d   %7.4f  %7.4f    %.4e      %.4e       %.4e'] 
7657              #'', 
7658              #'       X    H1       800  2048 0.8107 3.7310   4.9903e-03 9.8043e-04 5.2684e-02', 
7659              #'       Y    N15      128   256 0.7303 3.0331   3.1260e-02 7.8434e-03 1.3413e-01'] 
7660   
7661          for i, line in enumerate(show_apod_ver): 
7662              line_ver = get_output[i] 
7663   
7664              print(line) 
7665              if line[:50] == 'REMARK Noise Std Dev Before Processing H1 and N15:': 
7666                  continue 
7667              # Make the string test 
7668              self.assertEqual(line, line_ver) 
7669   
7670   
7671 -    def test_show_apod_rmsd(self): 
7672          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7673   
7674          # The path to the data files. 
7675          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7676   
7677          # Define file name. 
7678          file_name = '128_0_FT.ft2' 
7679   
7680          # Call function. 
7681          rmsd = show_apod_rmsd(file_name=file_name, dir=data_path) 
7682   
7683          # Assert. 
7684          self.assertEqual(rmsd, 8583.41) 
7685   
7686   
7687 -    def test_show_apod_rmsd_dir_to_files(self): 
7688          """Test searching for all NMRPipe spectrum files in dir, call showApod, and write to files.""" 
7689   
7690          # The path to the data files. 
7691          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7692   
7693          # Call function, and get all file names. 
7694          wfile_paths = show_apod_rmsd_dir_to_files(file_ext='.ft2', dir=data_path, outdir=self.tmpdir) 
7695   
7696          # Loop over file_paths. 
7697          for wfile_path in wfile_paths: 
7698              # Open the file. 
7699              get_data = extract_data(file=wfile_path) 
7700   
7701              # Extract line 0, column 0. 
7702              test = float(get_data[0][0]) 
7703   
7704              # Assert. 
7705              self.assertEqual(test, 8583.41) 
7706   
7707   
7708 -    def test_show_apod_rmsd_to_file(self): 
7709          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod, and write to file.""" 
7710   
7711          # The path to the data files. 
7712          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7713   
7714          # Define file name. 
7715          file_name = '128_0_FT.ft2' 
7716   
7717          # Call function, and get file name. 
7718          wfile_path = show_apod_rmsd_to_file(file_name=file_name, dir=data_path, outdir=self.tmpdir) 
7719   
7720          # Open the file. 
7721          get_data = extract_data(file=wfile_path) 
7722   
7723          # Extract line 0, column 0. 
7724          test = float(get_data[0][0]) 
7725   
7726          # Assert. 
7727          self.assertEqual(test, 8583.41) 
7728   
7729   
7730 -    def test_sod1wt_t25_bug_21954_order_error_analysis(self): 
7731          """Error analysis of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7732   
7733          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7734          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7735   
7736          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7737          Data is for experiment at 25 degree Celcius. 
7738   
7739          bug #21954 U{https://gna.org/bugs/index.php?21954}: Order of spectrum.error_analysis is important. 
7740          """ 
7741   
7742          # Base data setup. 
7743          pipe_name = 'base pipe' 
7744          pipe_type = 'relax_disp' 
7745          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7746          select_spin_index = list(range(0, 1)) 
7747          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7748   
7749          # Define replicated 
7750          repl_A = ['Z_A1', 'Z_A15'] 
7751          repl_B = ['Z_B1', 'Z_B18'] 
7752   
7753          # Loop over spectrum ID, and sort them 
7754          spectrum_ids_A = [] 
7755          spectrum_ids_B = [] 
7756          for spectrum_id in cdp.spectrum_ids: 
7757              if "A" in spectrum_id: 
7758                  spectrum_ids_A.append(spectrum_id) 
7759              elif "B" in spectrum_id: 
7760                  spectrum_ids_B.append(spectrum_id) 
7761   
7762          # To clean up old error analysis, delete attributes 
7763          delattr(cdp, "var_I") 
7764          delattr(cdp, "sigma_I") 
7765   
7766          # Perform error analysis 
7767          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7768          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7769   
7770          # Loop over spins, save errors to list 
7771          Errors_A_B = [] 
7772          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7773              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7774              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7775              Errors_A_B.append([A_err, B_err]) 
7776   
7777          # To clean up old error analysis, delete attributes 
7778          delattr(cdp, "var_I") 
7779          delattr(cdp, "sigma_I") 
7780   
7781          # Perform error analysis. Order is important 
7782          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7783          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7784   
7785          # Loop over spins, save errors to list 
7786          Errors_B_A = [] 
7787          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7788              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7789              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7790              Errors_B_A.append([A_err, B_err]) 
7791   
7792          # Make test for order of error 
7793          for i in range(len(Errors_A_B)): 
7794              Error_A_B = Errors_A_B[i] 
7795              Error_B_A = Errors_B_A[i] 
7796              self.assertAlmostEqual(Error_A_B[0], Error_B_A[0], 4) 
7797              self.assertAlmostEqual(Error_A_B[1], Error_B_A[1], 4) 
7798   
7799          # Make further tests for fixed values 
7800          std_A = math.sqrt((cdp.var_I[repl_A[0]] + cdp.var_I[repl_A[1]])/2) 
7801          std_A_fix = 2785.7263335738567 
7802   
7803          for id_A in spectrum_ids_A: 
7804              self.assertEqual(cdp.sigma_I[id_A], std_A) 
7805              self.assertAlmostEqual(cdp.sigma_I[id_A], std_A_fix, 7) 
7806   
7807          std_B = math.sqrt((cdp.var_I[repl_B[0]] + cdp.var_I[repl_B[1]])/2) 
7808          std_B_fix = 4967.3772030667988 
7809   
7810          for id_B in spectrum_ids_B: 
7811              self.assertEqual(cdp.sigma_I[id_B], std_B) 
7812              self.assertAlmostEqual(cdp.sigma_I[id_B], std_B_fix, 7) 
7813   
7814   
7815 -    def test_sod1wt_t25_to_cr72(self): 
7816          """Optimisation of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7817   
7818          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7819          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7820   
7821          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7822          Data is for experiment at 25 degree Celcius. 
7823          """ 
7824   
7825          # Base data setup. 
7826          pipe_name = 'base pipe' 
7827          pipe_type = 'relax_disp' 
7828          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7829          select_spin_index = list(range(0, 2)) 
7830          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7831   
7832          # Generate r20 key. 
7833          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7834          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7835   
7836          ## Now prepare for MODEL calculation. 
7837          MODEL = "CR72" 
7838   
7839          # Change pipe. 
7840          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7841          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7842          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7843   
7844          # Then select model. 
7845          self.interpreter.relax_disp.select_model(model=MODEL) 
7846   
7847          # GRID inc of 7 was found to be appropriate not to find pA = 0.5. 
7848          GRID_INC = 7 
7849   
7850          # Store grid and minimisations results. 
7851          grid_results = [] 
7852          mini_results = [] 
7853          clust_results = [] 
7854   
7855          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7856          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7857   
7858          # Deselect insignificant spins. 
7859          self.interpreter.relax_disp.insignificance(level=1.0) 
7860   
7861          # Perform Grid Search. 
7862          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7863   
7864          # Store result. 
7865          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7866              # Store grid results. 
7867              grid_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7868   
7869          ## Now do minimisation. 
7870          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7871          set_func_tol = 1e-9 
7872          set_max_iter = 100000 
7873          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7874   
7875          # Store result. 
7876          pA_values = [] 
7877          kex_values = [] 
7878          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7879              # Store minimisation results. 
7880              mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7881   
7882              # Store pA values. 
7883              pA_values.append(spin.pA) 
7884   
7885              # Store kex values. 
7886              kex_values.append(spin.kex) 
7887   
7888          print("\n# Now print before and after minimisation.\n") 
7889   
7890          # Print results. 
7891          for i in range(len(grid_results)): 
7892              # Get values. 
7893              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7894              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7895   
7896              print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7897              print("MIN  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7898   
7899          ## Prepare for clustering 
7900          # Change pipe. 
7901          pipe_name_MODEL_CLUSTER = "%s_%s_Cluster"%(pipe_name, MODEL) 
7902          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL_CLUSTER) 
7903          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL_CLUSTER) 
7904   
7905          # Then select model. 
7906          self.interpreter.relax_disp.select_model(model=MODEL) 
7907   
7908          # Define cluster id. 
7909          cluster_id = 'clust' 
7910   
7911          # Loop over spins to cluster them. 
7912          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7913              self.interpreter.relax_disp.cluster(cluster_id, spin_id) 
7914   
7915          # Copy over values. 
7916          self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL, pipe_to=pipe_name_MODEL_CLUSTER) 
7917   
7918          # Test the median values is correct 
7919          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7920              print(pA_values) 
7921              # The the median pA value returned. 
7922              self.assertEqual(median(pA_values), spin.pA) 
7923   
7924              # The the median kex value returned. 
7925              self.assertEqual(median(kex_values), spin.kex) 
7926   
7927          ## Now do minimisation. 
7928          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
7929   
7930          # Store result. 
7931          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7932              # Store clust results. 
7933              clust_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
7934   
7935              # Store the outcome of the clustering minimisation. 
7936              clust_pA = spin.pA 
7937              clust_kex = spin.kex 
7938   
7939          print("\n# Now testing.\n") 
7940   
7941          # Define results 
7942          test_res = {} 
7943          test_res[':10@N'] = {} 
7944          test_res[':10@N']['r2600'] = 18.429755324773360 
7945          test_res[':10@N']['r2500'] = 16.981349161968630 
7946          test_res[':10@N']['dw'] = 2.700755859433969 
7947          test_res[':10@N']['pA'] = 0.971531659288657 
7948          test_res[':10@N']['kex'] = 3831.766337047963134 
7949          test_res[':11@N'] = {} 
7950          test_res[':11@N']['r2600'] = 18.193409421115213 
7951          test_res[':11@N']['r2500'] = 17.308838135567765 
7952          test_res[':11@N']['dw'] = 2.706650302761793 
7953          test_res[':11@N']['pA'] = 0.971531659288657 
7954          test_res[':11@N']['kex'] = 3831.766337047963134 
7955   
7956          # Then make tests. 
7957          for i in range(len(grid_results)): 
7958              # Get values. 
7959              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
7960              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
7961              c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn = clust_results[i] 
7962   
7963              print("%s GRID   r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
7964              print("%s MIN    r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
7965              print("%s Clust  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn)) 
7966   
7967              # Make tests. 
7968              self.assertEqual(clust_pA, c_pA) 
7969              self.assertEqual(clust_kex, c_kex) 
7970   
7971              # Test values. 
7972              if c_spin_id in test_res: 
7973                  self.assertAlmostEqual(c_r2_600, test_res[c_spin_id]['r2600'], 4) 
7974                  self.assertAlmostEqual(c_r2_500, test_res[c_spin_id]['r2500'], 4) 
7975                  self.assertAlmostEqual(c_dw, test_res[c_spin_id]['dw'], 3) 
7976                  self.assertAlmostEqual(c_pA, test_res[c_spin_id]['pA'], 5) 
7977                  self.assertAlmostEqual(c_kex, test_res[c_spin_id]['kex'], 1) 
7978   
7979          # Save disp graph to temp. 
7980          #self.interpreter.relax_disp.plot_disp_curves(dir="~"+sep+"test", num_points=1000, extend=500.0, force=True). 
7981   
7982   
7983 -    def test_sod1wt_t25_to_sherekhan_input(self): 
7984          """Conversion of SOD1-WT CPMG R2eff values into input files for sherekhan. 
7985   
7986          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7987          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7988   
7989          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7990          Data is for experiment at 25 degree Celcius. 
7991          """ 
7992   
7993          # Base data setup. 
7994          pipe_name = 'base pipe' 
7995          pipe_type = 'relax_disp' 
7996          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7997          select_spin_index = list(range(0, 2)) 
7998          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7999   
8000          # Generate r20 key. 
8001          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
8002          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
8003   
8004          # Cluster everything, to analyse together. 
8005          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-1000") 
8006   
8007          # Write input 
8008          self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=ds.tmpdir) 
8009   
8010          # Check the r2eff set files. 
8011          print("\nChecking the R2eff input set files.") 
8012          files = [[ds.tmpdir + sep + 'cluster1', 'sherekhan_frq1.in'], [ ds.tmpdir + sep + 'cluster1', 'sherekhan_frq2.in']] 
8013   
8014          # First check file exists 
8015          for dir, file in files: 
8016              print(dir+sep+file) 
8017              self.assert_(access(dir+sep+file, F_OK)) 
8018   
8019          # Define how files should look like 
8020          data_set_600 = [ 
8021               "60.8272464287\n", 
8022               "0.06\n", 
8023               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
8024               "# G10\n", 
8025               "              33.333       26.53556078711      0.5236104771163\n", 
8026               "              66.667       25.29735243318        0.48766574122\n", 
8027               "                 100       25.09470361403      0.4820438864671\n", 
8028               "             133.333       25.15603274331      0.4837377286085\n", 
8029               "             166.667       24.27213341753      0.4599457904395\n", 
8030               "                 200       24.00364120328      0.4529773198905\n", 
8031               "             266.667       24.03511395168      0.4537880662536\n", 
8032               "                 300       23.04761040024      0.4291039120557\n", 
8033               "             333.333       22.95530300787      0.4268745963972\n", 
8034               "                 400       23.06158810662      0.4294426293624\n", 
8035               "             466.667       22.26799054092      0.4106809618644\n", 
8036               "             533.333       21.99851418823      0.4045232104735\n", 
8037               "             666.667       21.19651570955      0.3868136173831\n", 
8038               "             833.333       20.30938498379      0.3682604887899\n", 
8039               "                1000       20.28273252609       0.367719392568\n", 
8040               "# D11\n", 
8041               "              33.333       24.76520269878      0.5026475808706\n", 
8042               "              66.667        24.8773107448      0.5058752916906\n", 
8043               "                 100       24.90357815239      0.5066348551479\n", 
8044               "             133.333        23.7782506151      0.4751950583865\n", 
8045               "             166.667       23.68548762076      0.4727017128631\n", 
8046               "                 200       23.58629651618      0.4700517377679\n", 
8047               "             266.667       23.47734671187      0.4671601744044\n", 
8048               "                 300       24.08647493772      0.4835855560598\n", 
8049               "             333.333       22.98314371029      0.4542918950801\n", 
8050               "                 400       22.80339361568      0.4497107885587\n", 
8051               "             466.667       22.91634335366      0.4525833037874\n", 
8052               "             533.333       22.59774140046      0.4445334311324\n", 
8053               "             666.667        20.9177750759      0.4046955726046\n", 
8054               "             833.333       20.71792550566      0.4002363835007\n", 
8055               "                1000       19.54080006349      0.3751112751853\n", 
8056          ] 
8057   
8058          # Check data_set_600 
8059          file = open(files[0][0]+sep+files[0][1]) 
8060          lines = file.readlines() 
8061          file.close() 
8062          self.assertEqual(len(data_set_600), len(lines)) 
8063          for i in range(len(data_set_600)): 
8064              # Make the string test 
8065              self.assertEqual(data_set_600[i], lines[i]) 
8066   
8067          # Define how files should look like 
8068          data_set_500 = [ 
8069               "50.6846152368\n", 
8070               "0.04\n", 
8071               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
8072               "# G10\n", 
8073               "                  50       22.28084307393      0.2944966344183\n", 
8074               "                 100       21.93494977761      0.2910362768307\n", 
8075               "                 150       21.09850032232       0.282892238351\n", 
8076               "                 200       20.86493960397      0.2806737853646\n", 
8077               "                 250       20.75287269752      0.2796178205016\n", 
8078               "                 300       20.25597152406      0.2750013546989\n", 
8079               "                 350       19.92172163467      0.2719555756504\n", 
8080               "                 400       19.97712052922       0.272457105051\n", 
8081               "                 450       19.46807010415      0.2678972122793\n", 
8082               "                 500       19.76875460947      0.2705774849203\n", 
8083               "                 550       19.39161367402      0.2672216964327\n", 
8084               "                 600       19.03949517697      0.2641417899694\n", 
8085               "                 650       19.12218812132      0.2648605059901\n", 
8086               "                 700       19.01037461457      0.2638893584683\n", 
8087               "                 800       18.83395162904      0.2623674321143\n", 
8088               "                 900       18.47529972436      0.2593123604687\n", 
8089               "                1000        18.5252023121      0.2597343394038\n", 
8090               "# D11\n", 
8091               "                  50       22.15403890237      0.3285588379827\n", 
8092               "                 100       21.80946781746      0.3247185598713\n", 
8093               "                 150       21.77715415505       0.324361526682\n", 
8094               "                 200       21.41647464235      0.3204122024881\n", 
8095               "                 250       21.17099940822      0.3177616325958\n", 
8096               "                 300       21.03740030577      0.3163316496664\n", 
8097               "                 350       20.95393648281      0.3154427665172\n", 
8098               "                 400       20.93311399332       0.315221543436\n", 
8099               "                 450       20.18219905222      0.3073848655291\n", 
8100               "                 500       19.93599065085      0.3048744697057\n", 
8101               "                 550       19.68475725452      0.3023424499113\n", 
8102               "                 600       19.33575433934      0.2988741928798\n", 
8103               "                 650       19.53915692194      0.3008886196853\n", 
8104               "                 700        19.2018754351      0.2975587767134\n", 
8105               "                 800       18.82360965368      0.2938866923878\n", 
8106               "                 900       18.71861761238      0.2928790380131\n", 
8107               "                1000       17.95878049287      0.2857341721151\n", 
8108          ] 
8109   
8110          # Check data_set_500 
8111          file = open(files[1][0]+sep+files[1][1]) 
8112          lines = file.readlines() 
8113          file.close() 
8114          self.assertEqual(len(data_set_500), len(lines)) 
8115          for i in range(len(data_set_500)): 
8116              # Make the string test 
8117              self.assertEqual(data_set_500[i], lines[i]) 
8118   
8119          # Test local dir tests. This will be turned off in system test. 
8120          turn_on_local_dir_test = False 
8121   
8122          if turn_on_local_dir_test: 
8123              ## Now check to local folder with None argument. 
8124              # Write input 
8125              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None) 
8126   
8127              # Check the r2eff set files. 
8128              print("\nChecking the R2eff input set files.") 
8129              files = [[path.join(getcwd(), 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), 'cluster1'), 'sherekhan_frq2.in']] 
8130   
8131              # First check file exists 
8132              for dir, file in files: 
8133                  print(dir+sep+file) 
8134                  self.assert_(access(dir+sep+file, F_OK)) 
8135   
8136              ## Now check to local folder with dir argument. 
8137              # Write input 
8138              set_dir = "Test_ShereKhan" 
8139              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=set_dir) 
8140   
8141              # Check the r2eff set files. 
8142              print("\nChecking the R2eff input set files.") 
8143              files = [[path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq2.in']] 
8144   
8145              # First check file exists 
8146              for dir, file in files: 
8147                  print(dir+sep+file) 
8148                  self.assert_(access(dir+sep+file, F_OK)) 
8149   
8150   
8151 -    def test_sprangers_data_to_mmq_cr72(self, model=None): 
8152          """Test the 'MMQ CR72' model fitting against Remco Sprangers' ClpP data. 
8153   
8154          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MMQ CPMG data with a fixed relaxation time period. 
8155          """ 
8156   
8157          # Reset. 
8158          self.interpreter.reset() 
8159   
8160          # Create the data pipe and load the base data. 
8161          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8162          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8163   
8164          # The model data pipe. 
8165          model = 'MMQ CR72' 
8166          pipe_name = "%s - relax_disp" % model 
8167          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8168          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8169   
8170          # Set the model. 
8171          self.interpreter.relax_disp.select_model(model=model) 
8172   
8173          # Cluster everything. 
8174          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8175   
8176          # Copy the data. 
8177          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8178   
8179          # Alias the spins. 
8180          spin135S = cdp.mol[0].res[0].spin[0] 
8181          spin135F = cdp.mol[0].res[0].spin[1] 
8182          spin137S = cdp.mol[0].res[1].spin[0] 
8183          spin137F = cdp.mol[0].res[1].spin[1] 
8184   
8185          # The R20 keys. 
8186          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
8187          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8188   
8189          # Set the cluster specific parameters (only for the first spin). 
8190          spin135S.pA = 0.836591763632 
8191          spin135S.kex = 241.806525261 
8192   
8193          # Set the initial parameter values. 
8194          spin135S.r2 = {r20_key1: 28.2493431552, r20_key2: 31.7517334715} 
8195          spin135S.dw = 0.583003118785 
8196          spin135S.dwH = 0.0361441944301 
8197   
8198          spin135F.r2 = {r20_key1: 42.7201839991, r20_key2: 57.3178617389} 
8199          spin135F.dw = 0.805849745104 
8200          spin135F.dwH = 0.0215791945715 
8201   
8202          spin137S.r2 = {r20_key1: 26.0134115256, r20_key2: 30.575806934} 
8203          spin137S.dw = 0.688107568372 
8204          spin137S.dwH = 0.0344463604043 
8205   
8206          spin137F.r2 = {r20_key1: 46.6969397337, r20_key2: 58.602384101} 
8207          spin137F.dw = 0.94978299907 
8208          spin137F.dwH = 1.4818877939e-07 
8209   
8210          # Low precision optimisation. 
8211          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-10, max_iter=1000) 
8212   
8213          # Printout. 
8214          print("\n\nOptimised parameters:\n") 
8215          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8216          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8217          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8218          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8219          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8220          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8221          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8222          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8223          print("\n        # Set the cluster specific parameters (only for the first spin).") 
8224          print("        spin135S.pA = %s" % spin135S.pA) 
8225          print("        spin135S.kex = %s" % spin135S.kex) 
8226          print("\n        # Set the initial parameter values.") 
8227          print("        spin135S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135S.r2[r20_key1], spin135S.r2[r20_key2])) 
8228          print("        spin135S.dw = %s" % spin135S.dw) 
8229          print("        spin135S.dwH = %s" % spin135S.dwH) 
8230          print("\n        spin135F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135F.r2[r20_key1], spin135F.r2[r20_key2])) 
8231          print("        spin135F.dw = %s" % spin135F.dw) 
8232          print("        spin135F.dwH = %s" % spin135F.dwH) 
8233          print("\n        spin137S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137S.r2[r20_key1], spin137S.r2[r20_key2])) 
8234          print("        spin137S.dw = %s" % spin137S.dw) 
8235          print("        spin137S.dwH = %s" % spin137S.dwH) 
8236          print("\n        spin137F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137F.r2[r20_key1], spin137F.r2[r20_key2])) 
8237          print("        spin137F.dw = %s" % spin137F.dw) 
8238          print("        spin137F.dwH = %s" % spin137F.dwH) 
8239   
8240          # Checks for residue :135S. 
8241          self.assertAlmostEqual(spin135S.r2[r20_key1], 28.2493445347425, 4) 
8242          self.assertAlmostEqual(spin135S.r2[r20_key2], 31.7517352342937, 4) 
8243          self.assertAlmostEqual(spin135S.pA, 0.836591714049569, 4) 
8244          self.assertAlmostEqual(spin135S.dw, 0.583003004605869, 4) 
8245          self.assertAlmostEqual(spin135S.dwH, 0.0361441894065963, 4) 
8246          self.assertAlmostEqual(spin135S.kex/100, 241.806464344233/100, 4) 
8247          self.assertAlmostEqual(spin135S.chi2, 12.4224060116473, 4) 
8248   
8249          # Checks for residue :135F. 
8250          self.assertAlmostEqual(spin135F.r2[r20_key1], 42.7201844426839, 4) 
8251          self.assertAlmostEqual(spin135F.r2[r20_key2], 57.3178718548898, 4) 
8252          self.assertAlmostEqual(spin135F.pA, 0.836591714049569, 4) 
8253          self.assertAlmostEqual(spin135F.dw, 0.805849748711916, 4) 
8254          self.assertAlmostEqual(spin135F.dwH, 0.0215791669142752, 4) 
8255          self.assertAlmostEqual(spin135F.kex/100, 241.806464344233/100, 4) 
8256          self.assertAlmostEqual(spin135F.chi2, 12.4224060116473, 4) 
8257   
8258          # Checks for residue :137S. 
8259          self.assertAlmostEqual(spin137S.r2[r20_key1], 26.013412509919, 4) 
8260          self.assertAlmostEqual(spin137S.r2[r20_key2], 30.5758092335097, 4) 
8261          self.assertAlmostEqual(spin137S.pA, 0.836591714049569, 4) 
8262          self.assertAlmostEqual(spin137S.dw, 0.688107406812537, 4) 
8263          self.assertAlmostEqual(spin137S.dwH, 0.034446357344577, 4) 
8264          self.assertAlmostEqual(spin137S.kex/100, 241.806464344233/100, 4) 
8265          self.assertAlmostEqual(spin137S.chi2, 12.4224060116473, 4) 
8266   
8267          # Checks for residue :137F. 
8268          self.assertAlmostEqual(spin137F.r2[r20_key1], 46.696935090697, 4) 
8269          self.assertAlmostEqual(spin137F.r2[r20_key2], 58.6023842513446, 4) 
8270          self.assertAlmostEqual(spin137F.pA, 0.836591714049569, 4) 
8271          self.assertAlmostEqual(spin137F.dw, 0.94978325541294, 4) 
8272          self.assertAlmostEqual(spin137F.dwH, 1.5189362257653e-07, 4) 
8273          self.assertAlmostEqual(spin137F.kex/100, 241.806464344233/100, 4) 
8274          self.assertAlmostEqual(spin137F.chi2, 12.4224060116473, 4) 
8275   
8276   
8277 -    def test_sprangers_data_to_ns_mmq_2site(self, model=None): 
8278          """Test the 'NS MMQ 2-site' model fitting against Remco Sprangers' ClpP data. 
8279   
8280          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MQ CPMG data with a fixed relaxation time period. 
8281          """ 
8282   
8283          # Reset. 
8284          self.interpreter.reset() 
8285   
8286          # Create the data pipe and load the base data. 
8287          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8288          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8289   
8290          # The model data pipe. 
8291          model = 'NS MMQ 2-site' 
8292          pipe_name = "%s - relax_disp" % model 
8293          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8294          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8295   
8296          # Set the model. 
8297          self.interpreter.relax_disp.select_model(model=model) 
8298   
8299          # Cluster everything. 
8300          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8301   
8302          # Copy the data. 
8303          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8304   
8305          # Alias the spins. 
8306          spin135S = cdp.mol[0].res[0].spin[0] 
8307          spin135F = cdp.mol[0].res[0].spin[1] 
8308          spin137S = cdp.mol[0].res[1].spin[0] 
8309          spin137F = cdp.mol[0].res[1].spin[1] 
8310   
8311          # The R20 keys. 
8312          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8313          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8314   
8315          # Set the cluster specific parameters (only for the first spin). 
8316          spin135S.pA = 0.847378444499757 
8317          spin135S.kex = 264.055604934724329 
8318   
8319          # Set the initial parameter values. 
8320          spin135S.r2 = {r20_key1: 30.315119723745390, r20_key2: 37.411874745645299} 
8321          spin135S.dw = 0.585574008745351 
8322          spin135S.dwH = 0.000000000000002 
8323   
8324          spin135F.r2 = {r20_key1: 41.440843383778287, r20_key2: 56.989726795397893} 
8325          spin135F.dw = 0.856699277665748 
8326          spin135F.dwH = 0.000000000582587 
8327   
8328          spin137S.r2 = {r20_key1: 23.051695938570266, r20_key2: 28.352806483953824} 
8329          spin137S.dw = 0.772904450844973 
8330          spin137S.dwH = 0.183351478512970 
8331   
8332          spin137F.r2 = {r20_key1: 44.702032074210429, r20_key2: 56.453146052685319} 
8333          spin137F.dw = 0.984568590342831 
8334          spin137F.dwH = 0.000000001993458 
8335   
8336          # Low precision optimisation. 
8337          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-5, grad_tol=None, max_iter=100, constraints=True, scaling=True, verbosity=1) 
8338   
8339          # Printout. 
8340          print("\n\nOptimised parameters:\n") 
8341          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8342          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8343          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8344          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8345          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8346          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8347          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8348          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8349   
8350          # FIXME: Remove this temporary return and properly check the results. 
8351          return 
8352   
8353          # Checks for residue :135S. 
8354          self.assertAlmostEqual(spin135S.r2[r20_key1], 30.3151197237454, 4) 
8355          self.assertAlmostEqual(spin135S.r2[r20_key2], 37.4118747456453, 4) 
8356          self.assertAlmostEqual(spin135S.pA, 0.847378444499757, 4) 
8357          self.assertAlmostEqual(spin135S.dw, 0.585574008745351, 4) 
8358          self.assertAlmostEqual(spin135S.dwH, 2e-15, 4) 
8359          self.assertAlmostEqual(spin135S.kex, 264.055604934724, 4) 
8360          self.assertAlmostEqual(spin135S.chi2, 13.859423588071, 1) 
8361   
8362          # Checks for residue :135F. 
8363          self.assertAlmostEqual(spin135F.r2[r20_key1], 41.4408433837783, 4) 
8364          self.assertAlmostEqual(spin135F.r2[r20_key2], 56.9897267953979, 4) 
8365          self.assertAlmostEqual(spin135F.pA, 0.847378444499757, 4) 
8366          self.assertAlmostEqual(spin135F.dw, 0.856699277665748, 4) 
8367          self.assertAlmostEqual(spin135F.dwH, 5.82587e-10, 4) 
8368          self.assertAlmostEqual(spin135F.kex, 264.055604934724, 4) 
8369          self.assertAlmostEqual(spin135F.chi2, 13.859423588071, 1) 
8370   
8371          # Checks for residue :137S. 
8372          self.assertAlmostEqual(spin137S.r2[r20_key1], 23.0516959385703, 4) 
8373          self.assertAlmostEqual(spin137S.r2[r20_key2], 28.3528064839538, 4) 
8374          self.assertAlmostEqual(spin137S.pA, 0.847378444499757, 4) 
8375          self.assertAlmostEqual(spin137S.dw, 0.772904450844973, 4) 
8376          self.assertAlmostEqual(spin137S.dwH, 0.18335147851297, 4) 
8377          self.assertAlmostEqual(spin137S.kex, 264.055604934724, 4) 
8378          self.assertAlmostEqual(spin137S.chi2, 13.859423588071, 1) 
8379   
8380          # Checks for residue :137F. 
8381          self.assertAlmostEqual(spin137F.r2[r20_key1], 44.7020320742104, 4) 
8382          self.assertAlmostEqual(spin137F.r2[r20_key2], 56.4531460526853, 4) 
8383          self.assertAlmostEqual(spin137F.pA, 0.847378444499757, 4) 
8384          self.assertAlmostEqual(spin137F.dw, 0.984568590342831, 4) 
8385          self.assertAlmostEqual(spin137F.dwH, 2.0931309e-09, 4) 
8386          self.assertAlmostEqual(spin137F.kex, 264.055604934724, 4) 
8387          self.assertAlmostEqual(spin137F.chi2, 13.859423588071, 1) 
8388   
8389   
8390 -    def test_tp02_data_to_ns_r1rho_2site(self, model=None): 
8391          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
8392   
8393          # Setup the data. 
8394          self.setup_tp02_data_to_ns_r1rho_2site() 
8395   
8396          # Alias the spins. 
8397          spin1 = cdp.mol[0].res[0].spin[0] 
8398          spin2 = cdp.mol[0].res[1].spin[0] 
8399   
8400          # The R20 keys. 
8401          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8402          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8403   
8404          # Checks for residue :1. 
8405          self.assertAlmostEqual(spin1.r2[r20_key1], 8.50207717367548, 4) 
8406          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4680429589972, 4) 
8407          self.assertAlmostEqual(spin1.pA, 0.864523128842393, 4) 
8408          self.assertAlmostEqual(spin1.dw, 8.85204828994151, 4) 
8409          self.assertAlmostEqual(spin1.kex/1000, 1199.56359549637/1000, 4) 
8410          self.assertAlmostEqual(spin1.chi2, 2.99182130153514, 4) 
8411   
8412          # Checks for residue :2. 
8413          self.assertAlmostEqual(spin2.r2[r20_key1], 10.2099357790203, 4) 
8414          self.assertAlmostEqual(spin2.r2[r20_key2], 16.2137648697873, 4) 
8415          self.assertAlmostEqual(spin2.pA, 0.836488681031685, 4) 
8416          self.assertAlmostEqual(spin2.dw, 9.5505714779503, 4) 
8417          self.assertAlmostEqual(spin2.kex/1000, 1454.45726998929/1000, 4) 
8418          self.assertAlmostEqual(spin2.chi2, 0.000402231563481261, 4) 
8419   
8420   
8421 -    def test_tp02_data_to_ns_r1rho_2site_cluster(self, model=None): 
8422          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data, when performing clustering.""" 
8423   
8424          # Setup the data. 
8425          self.setup_tp02_data_to_ns_r1rho_2site(clustering=True) 
8426   
8427          # Alias the spins. 
8428          spin1 = cdp.mol[0].res[0].spin[0] 
8429          spin2 = cdp.mol[0].res[1].spin[0] 
8430   
8431          # The R20 keys. 
8432          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8433          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8434   
8435          # Checks for residue :1. 
8436          self.assertAlmostEqual(spin1.r2[r20_key1], 8.48607207881462, 4) 
8437          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4527609061722, 4) 
8438          self.assertAlmostEqual(spin1.pA, 0.863093838784425, 4) 
8439          self.assertAlmostEqual(spin1.dw, 8.86218096536618, 4) 
8440          self.assertAlmostEqual(spin1.kex/1000, 1186.22749648299/1000, 4) 
8441          self.assertAlmostEqual(spin1.chi2, 3.09500996065247, 4) 
8442   
8443          # Checks for residue :2. 
8444          self.assertAlmostEqual(spin2.r2[r20_key1], 10.4577906018883, 4) 
8445          self.assertAlmostEqual(spin2.r2[r20_key2], 16.4455550953792, 4) 
8446          self.assertAlmostEqual(spin2.pA, 0.863093838784425, 4) 
8447          self.assertAlmostEqual(spin2.dw, 11.5841168862587, 4) 
8448          self.assertAlmostEqual(spin2.kex/1000, 1186.22749648299/1000, 4) 
8449          self.assertAlmostEqual(spin2.chi2, 3.09500996065247, 4) 
8450   
8451   
8452 -    def test_tp02_data_to_mp05(self): 
8453          """Test the dispersion 'MP05' model fitting against the 'TP02' test data.""" 
8454   
8455          # Fixed time variable and the models. 
8456          ds.fixed = True 
8457          ds.models = ['R2eff', 'MP05'] 
8458   
8459          # Execute the script. 
8460          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8461   
8462          # Switch back to the data pipe for the optimisation. 
8463          self.interpreter.pipe.switch('MP05 - relax_disp') 
8464   
8465          # The equivalent MP05 parameters. 
8466          r1rho_prime = [[10.0058086343329, 15.005806870124], [12.0766320470785, 18.0767503536277]] 
8467          pA = [0.775055484521586, 0.500000000036595] 
8468          kex = [1235.20361276079, 2378.31403454691] 
8469          delta_omega = [7.08194146569694, 5.4083562844306] 
8470          chi2 = [0.0370400968727768, 0.182141732163934] 
8471   
8472          # Alias the spins. 
8473          spin1 = cdp.mol[0].res[0].spin[0] 
8474          spin2 = cdp.mol[0].res[1].spin[0] 
8475   
8476          # The R20 keys. 
8477          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8478          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8479   
8480          # Printout. 
8481          print("\n\nOptimised parameters:\n") 
8482          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8483          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8484          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8485          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8486          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8487          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8488          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8489   
8490          # Check each spin. 
8491          spin_index = 0 
8492          for spin, spin_id in spin_loop(return_id=True): 
8493              # Printout. 
8494              print("\nSpin %s." % spin_id) 
8495   
8496              # Check the fitted parameters. 
8497              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8498              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8499              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8500              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8501              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8502              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8503   
8504              # Increment the spin index. 
8505              spin_index += 1 
8506   
8507   
8508 -    def test_tp02_data_to_tap03(self): 
8509          """Test the dispersion 'TAP03' model fitting against the 'TP02' test data.""" 
8510   
8511          # Fixed time variable and the models. 
8512          ds.fixed = True 
8513          ds.models = ['R2eff', 'TAP03'] 
8514   
8515          # Execute the script. 
8516          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8517   
8518          # Switch back to the data pipe for the optimisation. 
8519          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8520   
8521          # The equivalent TAP03 parameters. 
8522          r1rho_prime = [[10.0058156589442, 15.005818505006], [12.0766046472748, 18.076648462452]] 
8523          pA = [0.775042569092891, 0.500000000229685] 
8524          kex = [1235.20852748765, 2379.47085580169] 
8525          delta_omega = [7.08176806468445, 5.40708372863538] 
8526          chi2 = [0.0371366837083293, 0.182212857256044] 
8527   
8528          # Alias the spins. 
8529          spin1 = cdp.mol[0].res[0].spin[0] 
8530          spin2 = cdp.mol[0].res[1].spin[0] 
8531   
8532          # The R20 keys. 
8533          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8534          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8535   
8536          # Printout. 
8537          print("\n\nOptimised parameters:\n") 
8538          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8539          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8540          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8541          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8542          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8543          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8544          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8545   
8546          # Switch to the 'MP05' model data pipe, then check for each spin. 
8547          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8548          spin_index = 0 
8549          for spin, spin_id in spin_loop(return_id=True): 
8550              # Printout. 
8551              print("\nSpin %s." % spin_id) 
8552   
8553              # Check the fitted parameters. 
8554              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8555              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8556              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8557              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8558              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8559              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8560   
8561              # Increment the spin index. 
8562              spin_index += 1 
8563   
8564   
8565 -    def test_task_7882_monte_carlo_std_residual(self): 
8566          """Implementation of Task #7882 U{https://gna.org/task/?7882}: Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals""" 
8567   
8568          # First check that results are stored with minimisation, to make sure that Sum of Squares are stored (Chi2 without weighting) and degrees of freedom (dof) is stored. 
8569   
8570          # Load the results file from a clustered minimisation. 
8571          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'error_testing'+sep+'task_7882' 
8572          self.interpreter.results.read(file_name) 
8573   
8574          # Get the spins, which was used for clustering. 
8575          spins_cluster = cdp.clustering['sel'] 
8576          spins_free = cdp.clustering['free spins'] 
8577   
8578          # For sanity check, calculate degree of freedom. 
8579          cur_spin_id = spins_cluster[0] 
8580          cur_spin = return_spin(cur_spin_id) 
8581   
8582          # Calculate total number of datapoins. 
8583          N = len(spins_cluster) 
8584          N_dp = N * len(cur_spin.r2eff) 
8585   
8586          # Calculate number of paramaters. For CR72, there is R2 per spectrometer field, individual dw, and shared kex and pA. 
8587          N_par = cdp.spectrometer_frq_count * N + N + 1 + 1 
8588          dof = N_dp - N_par 
8589   
8590          # Sanity check of parameters. 
8591          print(N_par, N_dp) 
8592   
8593          # Number of MC 
8594          mc_nr = 3 
8595   
8596          # Setup MC for errors generated from the distribution described by chi2 and degrees of freedom from best fit. 
8597          self.interpreter.monte_carlo.setup(number=mc_nr) 
8598   
8599          # Create data. 
8600          self.interpreter.monte_carlo.create_data(distribution="red_chi2") 
8601   
8602          # Setup MC again. 
8603          self.interpreter.monte_carlo.setup(number=mc_nr) 
8604   
8605          # Create data, and set the fixed error value, without setting the correct distribution. 
8606          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, fixed_error=1.) 
8607   
8608          # Setup MC again. 
8609          self.interpreter.monte_carlo.setup(number=mc_nr) 
8610   
8611          # Create data, with fixed error distribution, but not setting the error value. 
8612          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, distribution="fixed") 
8613   
8614          # Setup MC again. 
8615          self.interpreter.monte_carlo.create_data(distribution="fixed", fixed_error=1.) 
8616   
8617          # Now select the R2eff model, and try again. Expect raising an error. 
8618          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
8619   
8620          # Setup MC again. 
8621          self.interpreter.monte_carlo.setup(number=mc_nr) 
8622   
8623          # Create data, and assert failure. 
8624          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, distribution="red_chi2") 
8625          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, method="direct", distribution="red_chi2") 
8626   
8627   
8628 -    def x_test_task_7882_kex_conf(self): 
8629          """Test related to Task #7882 U{https://gna.org/task/?7882}: Try making a confidence interval of kex. 
8630          According to the regression book of Graphpad: U{http://www.graphpad.com/faq/file/Prism4RegressionBook.pdf}. 
8631          Page 109-111. 
8632          """ 
8633   
8634          # Load the results file from a clustered minimisation. 
8635          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'error_testing'+sep+'task_7882' 
8636          self.interpreter.results.read(file_name) 
8637   
8638          # Get the spins, which was used for clustering. 
8639          spins_cluster = cdp.clustering['sel'] 
8640          spins_free = cdp.clustering['free spins'] 
8641   
8642          # For sanity check, calculate degree of freedom. 
8643          cur_spin_id = spins_cluster[0] 
8644          cur_spin = return_spin(cur_spin_id) 
8645   
8646          # Calculate total number of datapoins. 
8647          Ns = len(spins_cluster) 
8648          N_dp = Ns * len(cur_spin.r2eff) 
8649   
8650          # Calculate number of paramaters. For CR72, there is R2 per spectrometer field, individual dw, and shared kex and pA. 
8651          N_par = cdp.spectrometer_frq_count * Ns + Ns + 1 + 1 
8652          dof_fit = N_dp - N_par 
8653   
8654          # Assert values. 
8655          self.assertEqual(Ns, 61) 
8656          self.assertEqual(N_dp, 1952) 
8657          self.assertEqual(N_par, 185) 
8658   
8659          # Confidence interval of kex. 
8660          # The number of parameters to check is kex = 1. 
8661          P = 1 
8662          # Number of datapoints 
8663          N = N_dp 
8664          # The degrees of freedom for this confidence interval 
8665          dof_conf = N - P 
8666   
8667          # The critical value of the F distribution with p-value of 0.05 for 95% confidence. 
8668          # Can be calculated with microsoft excel: 
8669          # F=FINV(0,05; P; dof_conf), F=FINV(0,05; P; dof_conf), F=FINV(0,05; 1; 1951)=3,846229551 
8670          # Can also be calculated with: import scipy.stats; scipy.stats.f.isf(0.05, 1, 1951)=3.8462295505435562 
8671          F = 3.8462295505435562 
8672          # Then calculate the scaling of chi2, which is the weighted sum of squares of best fit. 
8673          scale = F*P/dof_conf +1 
8674   
8675          # Get the sum of best fit. 
8676          SSbest_fit = cur_spin.chi2 
8677          SSbest_kex = cur_spin.kex 
8678   
8679          # Get the scaled sum of best fit 
8680          SSall_fixed = SSbest_fit * scale 
8681   
8682          print(SSbest_fit, scale, SSall_fixed) 
8683   
8684          # Now generate a list of kex values to try. 
8685          kex_cur = cur_spin.kex 
8686          kex_list = linspace(kex_cur - 1500, kex_cur + 3000, 200) 
8687   
8688          chi2_list = [] 
8689   
8690          for kex in kex_list: 
8691              self.interpreter.value.set(val=kex, param='kex') 
8692   
8693              # Calculate the chi2 values. 
8694              self.interpreter.minimise.calculate(verbosity=0) 
8695   
8696              # Get the chi2 value 
8697              chi2_cur = cur_spin.chi2 
8698              print("kex=%3.2f, chi2=%3.2f"%(kex, chi2_cur), chi2_cur<SSall_fixed) 
8699   
8700              # Add to list 
8701              chi2_list.append(chi2_cur) 
8702   
8703          # Now make to numpy array. 
8704          chi2_list = asarray(chi2_list) 
8705   
8706          # Now make a selection mask based on the criteria. 
8707          sel_mask = chi2_list < SSall_fixed 
8708   
8709          # Select values of kex, and chi2_list 
8710          kex_sel = kex_list[sel_mask] 
8711          chi2_sel = chi2_list[sel_mask] 
8712   
8713          # Now make plot 
8714          print(SSbest_kex, SSbest_fit, SSall_fixed) 
8715          print(kex_sel) 
8716          print(chi2_sel) 
8717   
8718          if True: 
8719              import matplotlib.pyplot as plt 
8720   
8721              plt.plot(kex_sel, chi2_sel, "bo") 
8722              plt.plot(SSbest_kex, SSbest_fit, "g*") 
8723              plt.show() 
8724   
8725   
8726 -    def test_tp02_data_to_tp02(self): 
8727          """Test the relaxation dispersion 'TP02' model curve fitting to fixed time synthetic data.""" 
8728   
8729          # Fixed time variable. 
8730          ds.fixed = True 
8731   
8732          # Execute the script. 
8733          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8734   
8735          # The original parameters. 
8736          r1rho_prime = [[10.0, 15.0], [12.0, 18.0]] 
8737          pA = 0.7654321 
8738          kex = 1234.56789 
8739          delta_omega = [7.0, 9.0] 
8740   
8741          # The R20 keys. 
8742          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8743          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8744   
8745          # Switch to the 'TP02' model data pipe, then check for each spin. 
8746          self.interpreter.pipe.switch('TP02 - relax_disp') 
8747          spin_index = 0 
8748          for spin, spin_id in spin_loop(return_id=True): 
8749              # Printout. 
8750              print("\nSpin %s." % spin_id) 
8751   
8752              # Check the fitted parameters. 
8753              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8754              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8755              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8756              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 3) 
8757   
8758              # Increment the spin index. 
8759              spin_index += 1 
8760   
8761   
8762 -    def test_value_write_calc_rotating_frame_params_int(self): 
8763          """System test of the value.write function to write intensities for an R1rho setup. 
8764          This system test is to make sure, that modifying the API for special parameters theta and w_eff does not alter the functionality value.write. 
8765   
8766          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8767          """ 
8768   
8769          # Load the state. 
8770          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8771          self.interpreter.state.load(statefile, force=True) 
8772   
8773          # Set filepaths. 
8774          int_filepath = ds.tmpdir+sep+'int.out' 
8775   
8776          # Write out the intensity parameter file. 
8777          # The writing out of intensity file is to make sure the API function retains its function after modification for special parameters. 
8778          self.interpreter.value.write(param='peak_intensity', file='int.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8779   
8780          # Test the file exists. 
8781          self.assert_(access(int_filepath, F_OK)) 
8782   
8783          # Open the files for testing. 
8784          int_file = open(int_filepath, 'r') 
8785   
8786          # Loop over the intensity file to test values. 
8787          for line in int_file: 
8788              # Skip lines starting with #. 
8789              if line[0] == "#": 
8790                  continue 
8791   
8792              # Split the line 
8793              linesplit = line.split() 
8794   
8795              # Assume values 
8796              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8797                  self.assertEqual(linesplit[5], "115571.4") 
8798              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8799                  self.assertEqual(linesplit[5], "68377.52") 
8800              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8801                  self.assertEqual(linesplit[5], "9141.689") 
8802              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8803                  self.assertEqual(linesplit[5], "29123.77") 
8804              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8805                  self.assertEqual(linesplit[5], "58914.94") 
8806   
8807          # Close files 
8808          int_file.close() 
8809   
8810   
8811 -    def test_value_write_calc_rotating_frame_params_theta(self): 
8812          """System test of the value.write function to write return values of theta from calc_rotating_frame_params() function for an R1rho setup. 
8813   
8814          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8815          """ 
8816   
8817          # Load the state. 
8818          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8819          self.interpreter.state.load(statefile, force=True) 
8820   
8821          # Set filepaths. 
8822          theta_filepath = ds.tmpdir+sep+'theta.out' 
8823   
8824          # Write out the theta parameter file. 
8825          self.interpreter.value.write(param='theta', file='theta.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8826   
8827          # Test the file exists. 
8828          self.assert_(access(theta_filepath, F_OK)) 
8829   
8830          # Open the files for testing. 
8831          theta_file = open(theta_filepath, 'r') 
8832   
8833          # Loop over the theta file to test values. 
8834          for line in theta_file: 
8835              # Skip lines starting with #. 
8836              if line[0] == "#": 
8837                  continue 
8838              # Print lines, not including newline character. 
8839              print(line[:-1]) 
8840   
8841              # Split the line 
8842              linesplit = line.split() 
8843   
8844              # Assume values 
8845              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8846                  self.assertNotEqual(linesplit[5], "None") 
8847              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8848                  self.assertNotEqual(linesplit[5], "None") 
8849              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8850                  self.assertNotEqual(linesplit[5], "None") 
8851              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8852                  self.assertNotEqual(linesplit[5], "None") 
8853              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8854                  self.assertNotEqual(linesplit[5], "None") 
8855   
8856          # Close files 
8857          theta_file.close() 
8858   
8859   
8860 -    def test_value_write_calc_rotating_frame_params_w_eff(self): 
8861          """System test of the value.write function to write return values of w_eff from calc_rotating_frame_params() function for an R1rho setup. 
8862   
8863          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8864          """ 
8865   
8866          # Load the state. 
8867          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8868          self.interpreter.state.load(statefile, force=True) 
8869   
8870          # Set filepaths. 
8871          w_eff_filepath = ds.tmpdir+sep+'w_eff.out' 
8872   
8873          # Write out the w_eff parameter file. 
8874          self.interpreter.value.write(param='w_eff', file='w_eff.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8875   
8876          # Test the file exists. 
8877          self.assert_(access(w_eff_filepath, F_OK)) 
8878   
8879          # Open the files for testing. 
8880          w_eff_file = open(w_eff_filepath, 'r') 
8881   
8882          # Loop over the w_eff file to test values. 
8883          for line in w_eff_file: 
8884              # Skip lines starting with #. 
8885              if line[0] == "#": 
8886                  continue 
8887              # Print lines, not including newline character. 
8888              print(line[:-1]) 
8889   
8890              # Split the line 
8891              linesplit = line.split() 
8892   
8893              # Assume values 
8894              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8895                  self.assertNotEqual(linesplit[5], "None") 
8896              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8897                  self.assertNotEqual(linesplit[5], "None") 
8898              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8899                  self.assertNotEqual(linesplit[5], "None") 
8900              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8901                  self.assertNotEqual(linesplit[5], "None") 
8902              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8903                  self.assertNotEqual(linesplit[5], "None") 
8904   
8905          # Close files 
8906          w_eff_file.close() 
8907   
8908   
8909 -    def test_value_write_calc_rotating_frame_params_auto_analysis(self): 
8910          """System test of the auto_analysis value.write function to write theta and w_eff values for an R1rho setup. 
8911   
8912          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8913          """ 
8914   
8915          # Load the state. 
8916          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344.bz2' 
8917          self.interpreter.state.load(statefile, force=True) 
8918   
8919          # Set pipe name, bundle and type. 
8920          pipe_name = 'base pipe' 
8921          pipe_bundle = 'relax_disp' 
8922          pipe_type = 'relax_disp' 
8923   
8924          # The path to the data files. 
8925          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
8926   
8927          # Deselect all spins 
8928          self.interpreter.deselect.all() 
8929   
8930          # Specify spins to be selected. 
8931          select_spin_ids = [ 
8932          ":13@N", 
8933          ":15@N", 
8934          ":16@N", 
8935          ":25@N", 
8936          ":26@N", 
8937          ":28@N", 
8938          ":39@N", 
8939          ":40@N", 
8940          ":41@N", 
8941          ":43@N", 
8942          ":44@N", 
8943          ":45@N", 
8944          ":49@N", 
8945          ":52@N", 
8946          ":53@N"] 
8947   
8948          # Reverse the selection for the spins. 
8949          for curspin in select_spin_ids: 
8950              print("Selecting spin %s"%curspin) 
8951              self.interpreter.deselect.reverse(spin_id=curspin) 
8952   
8953          # Read the R1 data 
8954          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
8955   
8956          # The dispersion models. 
8957          MODELS = ['R2eff'] 
8958   
8959          # The grid search size (the number of increments per dimension). 
8960          GRID_INC = 4 
8961   
8962          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
8963          MC_NUM = 3 
8964   
8965          # Model selection technique. 
8966          MODSEL = 'AIC' 
8967   
8968          # Execute the auto-analysis (fast). 
8969          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
8970          OPT_FUNC_TOL = 1e-1 
8971          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
8972          OPT_MAX_ITERATIONS = 1000 
8973          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
8974   
8975          # Run the analysis. 
8976          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
8977   
8978          ## Check for file creation 
8979          # Set filepaths. 
8980          theta_filepath = ds.tmpdir+sep+MODELS[0]+sep+'theta.out' 
8981          w_eff_filepath = ds.tmpdir+sep+MODELS[0]+sep+'w_eff.out' 
8982   
8983          # Test the files exists. 
8984          self.assert_(access(theta_filepath, F_OK)) 
8985          self.assert_(access(w_eff_filepath, F_OK)) 
8986   
8987          # Open the files for testing. 
8988          theta_file = open(theta_filepath, 'r') 
8989          theta_result = [ 
8990              "# Parameter description:  Rotating frame tilt angle : ( theta = arctan(w_1 / Omega) ) (rad).\n", 
8991              "#\n", 
8992              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
8993              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8994              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8995              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8996              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8997              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8998              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
8999              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9000              "None          13         L           None        N                1.83827367612531                   None                                           1.79015307643158                   None                                            2.2768687598681                  None                                          2.08461171779445                  None                                          2.00120623474388                  None                                          1.92825070277699                  None                                          1.47212860033516                   None                                           1.12978017906854                   None                                           1.20415336139956                   None                                          0.901691390796334                  None                                         0.687390207543568                   None                                          0.455635480573046                  None                                         0.281637123971289                   None                                          0.138259661766539                   None                                       \n", 
9001              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9002              "None          15         R           None        N                1.58367544790673                   None                                           1.58127411936947                   None                                           1.61085209029811                  None                                          1.59731540507347                  None                                          1.59237108385522                  None                                          1.58834866344307                  None                                           1.2251048782537                   None                                          0.938142786712004                   None                                           1.03297495592991                   None                                          0.683284686224254                  None                                         0.594447788256641                   None                                          0.383528609383686                  None                                         0.262780814059893                   None                                          0.133469839450564                   None                                       \n", 
9003              "None          16         T           None        N                1.40984232256624                   None                                           1.43947245672073                   None                                           1.10299856647417                  None                                          1.24811470332083                  None                                          1.30521602599932                  None                                          1.35302443831853                  None                                          1.07923777467974                   None                                          0.833345927788896                   None                                          0.934350308974616                   None                                          0.581325254389991                  None                                         0.543659670184793                   None                                          0.346238480454282                  None                                         0.251454336191817                   None                                          0.130436714663781                   None                                       \n", 
9004              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9005              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9006              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9007              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9008              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9009              "None          25         Q           None        N                1.81569700258844                   None                                           1.77137827615015                   None                                           2.23175875585624                  None                                          2.04612705363098                  None                                           1.9673155780155                  None                                          1.89908711012298                  None                                          1.44829660124856                   None                                           1.11023386429581                   None                                           1.18716091371256                   None                                          0.877306975624962                  None                                         0.677790118853413                   None                                          0.447932002242236                  None                                         0.279785379050945                   None                                          0.137802891887767                   None                                       \n", 
9010              "None          26         Q           None        N                1.61128821168674                   None                                           1.60374392042003                   None                                           1.69619923953765                  None                                          1.65403989292986                  None                                          1.63856717205868                  None                                          1.62595755714564                  None                                          1.24977859227795                   None                                          0.956353494917591                   None                                           1.04972090035774                   None                                          0.702164059520172                  None                                         0.603227813742091                   None                                          0.390116910781037                  None                                         0.264658552037535                   None                                          0.133960994297096                   None                                       \n", 
9011              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9012              "None          28         Q           None        N                1.65182797011356                   None                                           1.63676707684161                   None                                           1.81830827892972                  None                                           1.7365089711986                  None                                          1.70601955220877                  None                                          1.68102938663686                  None                                          1.28685736157369                   None                                          0.984047498595701                   None                                            1.0749792109454                   None                                          0.731585685663053                  None                                         0.616577997665602                   None                                          0.400219205533665                  None                                         0.267471993812649                   None                                          0.134690869499646                   None                                       \n", 
9013              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9014              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9015              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9016              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9017              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9018              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9019              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9020              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9021              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9022              "None          39         L           None        N                1.76426439181176                   None                                           1.72885318885161                   None                                           2.11826300085737                  None                                          1.95430201082222                  None                                          1.88794717058464                  None                                          1.83172922971397                  None                                          1.39549951193417                   None                                           1.06783946148624                   None                                           1.14997013232702                   None                                          0.826128785942585                  None                                         0.657105386950171                   None                                          0.431542911580536                  None                                         0.275725736430539                   None                                          0.136791385554619                   None                                       \n", 
9023              "None          40         M           None        N                 1.5521741199158                   None                                           1.55564594516135                   None                                           1.51290906497298                  None                                          1.53245929150759                  None                                          1.53960430408466                  None                                          1.54541832596591                  None                                          1.19750223001929                   None                                          0.917959090226757                   None                                           1.01428385962747                   None                                          0.662779584695967                  None                                         0.584708929219264                   None                                          0.376271266885303                  None                                         0.260671619214194                   None                                          0.132914250767089                   None                                       \n", 
9024              "None          41         A           None        N                1.68339451828261                   None                                           1.66252964414082                   None                                           1.90911961276946                  None                                          1.79959323497326                  None                                          1.75801925517113                  None                                          1.72370710837265                  None                                          1.31646868936419                   None                                           1.00647189763597                   None                                           1.09525348649914                   None                                           0.75605702767542                  None                                         0.627395557358039                   None                                          0.408481831044309                  None                                         0.269716174238842                   None                                          0.135267948387412                   None                                       \n", 
9025              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9026              "None          43         F           None        N                1.58506597154432                   None                                           1.58240542750303                   None                                           1.61517196062351                  None                                          1.60017740004898                  None                                          1.59469990835425                  None                                          1.59024353162528                  None                                          1.22633651794829                   None                                          0.939047922181951                   None                                           1.03380990731605                   None                                          0.684214484755514                  None                                         0.594884298549546                   None                                          0.383855128702894                  None                                         0.262874695048502                   None                                           0.13349447283116                   None                                       \n", 
9027              "None          44         I           None        N                1.57575471961837                   None                                           1.57483015671791                   None                                           1.58622388390755                  None                                          1.58100758841935                  None                                          1.57910319967536                  None                                          1.57755415552211                  None                                          1.21811077066835                   None                                          0.933010299763027                   None                                           1.02823520295828                   None                                           0.67802911457195                  None                                         0.591972285081647                   None                                          0.381678892926696                  None                                         0.262247347241724                   None                                          0.133329708422379                   None                                       \n", 
9028              "None          45         K           None        N                1.77147501495754                   None                                           1.73479633022489                   None                                           2.13509660780385                  None                                          1.96751045408372                  None                                          1.89924480319914                  None                                          1.84124387452692                  None                                          1.40277881643715                   None                                           1.07361367582571                   None                                           1.15506365550891                   None                                          0.832963505534767                  None                                         0.659913187081268                   None                                          0.433751178249555                  None                                         0.276282572106685                   None                                           0.13693095791902                   None                                       \n", 
9029              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9030              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9031              "None          49         A           None        N                2.00297059962685                   None                                           1.92978318052058                   None                                           2.53305709323468                  None                                          2.33052197276846                  None                                          2.22870514722639                  None                                          2.13201782446864                  None                                           1.6587904412969                   None                                           1.29333162369472                   None                                           1.34311052758116                   None                                           1.12559033900783                  None                                         0.770195063841652                   None                                          0.524846264860003                  None                                         0.296857751274362                   None                                          0.141908833673671                   None                                       \n", 
9032              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9033              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9034              "None          52         V           None        N                1.82421571143794                   None                                           1.77845404105203                   None                                           2.24910726268822                  None                                          2.06078232916932                  None                                          1.98017451806059                  None                                          1.91012195713554                  None                                          1.45724107606646                   None                                           1.11753869321304                   None                                           1.19352234944057                   None                                          0.886361068343012                  None                                         0.681372607920812                   None                                          0.450799407357501                  None                                         0.280478735779163                   None                                          0.137974257665877                   None                                       \n", 
9035              "None          53         A           None        N                2.05019708195234                   None                                           1.97089957318506                   None                                           2.58789168363698                  None                                          2.39027806684801                  None                                          2.28731354878582                  None                                           2.1872118539319                  None                                           1.7165709935896                   None                                           1.34832362477229                   None                                           1.38879751095815                   None                                            1.2085314357749                  None                                         0.799450059125864                   None                                          0.550583841461621                  None                                          0.30195492609136                   None                                          0.143090604877102                   None                                       \n", 
9036              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9037              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9038              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9039              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9040              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
9041          ] 
9042          # Check the created theta file. 
9043          lines = theta_file.readlines() 
9044          for i in range(len(lines)): 
9045              # Test lines starting with # 
9046              if theta_result[i][0] == "#": 
9047                  self.assertEqual(theta_result[i], lines[i]) 
9048              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
9049              if theta_result[i] == lines[i]: 
9050                  self.assertEqual(theta_result[i], lines[i]) 
9051              # If the line is not equal each other, make a slower comparison of values. 
9052              else: 
9053                  # Print lines if they don't match. To help find differences. 
9054                  print(theta_result[i]) 
9055                  print(lines[i]) 
9056   
9057                  # First test first 62 characters containing spin information 
9058                  self.assertEqual(theta_result[i][:62], lines[i][:62]) 
9059   
9060                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
9061                  theta_result_s = theta_result[i][62:].split()[::2] 
9062                  print(theta_result_s ) 
9063                  lines_s = lines[i][62:].split()[::2] 
9064                  print(lines_s) 
9065                  # Loop over the value elements 
9066                  for j in range(len(lines_s)): 
9067                      print(theta_result_s[j], lines_s[j]) 
9068                      # Assume a precision to digits. 
9069                      self.assertAlmostEqual(float(theta_result_s[j]), float(lines_s[j]), 14) 
9070   
9071          # Close file 
9072          theta_file.close() 
9073   
9074          w_eff_file = open(w_eff_filepath, 'r') 
9075          w_eff_result = [ 
9076              "# Parameter description:  Effective field in rotating frame : ( w_eff = sqrt(Omega^2 + w_1^2) ) (rad.s^-1).\n", 
9077              "#\n", 
9078              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
9079              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9080              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9081              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9082              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9083              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9084              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9085              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9086              "None          13         L           None        N                8737.12883908829                   None                                           10612.1226552258                   None                                           3558.93734069587                  None                                          4698.27194621826                  None                                          5534.46153956037                  None                                          6599.82570817753                  None                                          8467.62674839481                   None                                           9318.00441649087                   None                                           11095.2662520767                   None                                           6412.33580591254                  None                                          13279.9803044242                   None                                            11430.254637056                  None                                          30318.7268264644                   None                                           61141.1080046448                   None                                       \n", 
9087              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9088              "None          15         R           None        N                8427.14155005377                   None                                           10358.3995676635                   None                                           2710.22680763322                  None                                          4093.04942975722                  None                                          5030.86065069262                  None                                          6183.60685459024                  None                                          8956.28403254202                   None                                           10448.6627754369                   None                                           12060.4428066937                   None                                           7966.64282975241                  None                                          15045.8392092364                   None                                           13441.3586252373                  None                                          32438.4764809909                   None                                           63321.5201471181                   None                                       \n", 
9089              "None          16         T           None        N                 8536.7818857229                   None                                            10447.792678989                   None                                           3034.01707453628                  None                                           4314.2767521567                  None                                          5212.43600885913                  None                                          6332.21319855067                  None                                          9558.14311447582                   None                                           11384.2336494604                   None                                           12879.4604966293                   None                                           9159.34604475399                  None                                          16290.1746838959                   None                                           14821.0200530829                  None                                          33866.5933527757                   None                                           64785.3205696403                   None                                       \n", 
9090              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9091              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9092              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9093              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9094              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9095              "None          25         Q           None        N                8685.60895531182                   None                                           10569.7459677762                   None                                           3430.51272680396                  None                                          4601.75421490393                  None                                          5452.76508815826                  None                                          6531.46859076009                  None                                          8490.06475886501                   None                                           9406.58372902508                   None                                           11169.7602637607                   None                                           6540.38696356753                  None                                          13437.7348017798                   None                                           11613.1632549021                  None                                          30514.0741594726                   None                                           61342.4792156782                   None                                       \n", 
9096              "None          26         Q           None        N                8433.35533683544                   None                                           10363.4554631194                   None                                           2729.48656005151                  None                                          4105.82770792005                  None                                          5041.26238350827                  None                                          6192.07245313098                  None                                          8880.08366342131                   None                                           10312.6868786802                   None                                           11942.8320576165                   None                                           7787.44854491812                  None                                          14853.4987024375                   None                                           13225.7048162038                  None                                          32213.6690023282                   None                                           63090.7407990801                   None                                       \n", 
9097              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9098              "None          28         Q           None        N                8454.18308422202                   None                                           10380.4112885894                   None                                           2793.17494362899                  None                                          4148.43953208179                  None                                          5076.02756135055                  None                                          6220.40920270029                  None                                          8777.91538040813                   None                                           10118.8737706315                   None                                           11775.8792998529                   None                                           7528.90766101027                  None                                          14572.4015102398                   None                                            12909.211050939                  None                                          31882.8171856889                   None                                           62750.9120842199                   None                                       \n", 
9099              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9100              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9101              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9102              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9103              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9104              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9105              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9106              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9107              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9108              "None          39         L           None        N                 8586.6405431352                   None                                           10488.5710521378                   None                                           3171.59430904777                  None                                          4412.11227722123                  None                                          5293.69814015286                  None                                          6399.27143075725                  None                                          8557.58926327909                   None                                           9617.45773774313                   None                                           11347.9169998729                   None                                           6840.20010813426                  None                                          13795.1250622375                   None                                           12024.9041436853                  None                                           30951.651485352                   None                                           61793.2130509111                   None                                       \n", 
9109              "None          40         M           None        N                8427.90394711227                   None                                           10359.0198301036                   None                                           2712.59646573568                  None                                          4094.61889210019                  None                                          5032.13762965554                  None                                           6184.6458240746                  None                                          9049.68452800053                   None                                           10607.7913029633                   None                                           12198.5639821231                   None                                           8174.23271685285                  None                                          15266.4924700447                   None                                           13687.9010998756                  None                                          32694.9043143038                   None                                           63584.6371927381                   None                                       \n", 
9110              "None          41         A           None        N                8480.14299737436                   None                                           10401.5648897003                   None                                           2870.79081440785                  None                                          4201.09083283266                  None                                          5119.14733505123                  None                                          6255.64579267482                  None                                          8706.50768957471                   None                                           9972.71017314947                   None                                           11650.5225246067                   None                                           7331.28858930568                  None                                          14354.1616183112                   None                                           12662.3378547029                  None                                          31623.9195264738                   None                                           62484.8290612112                   None                                       \n", 
9111              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9112              "None          43         F           None        N                8427.30062786474                   None                                           10358.5289868368                   None                                            2710.7214015056                  None                                          4093.37694357637                  None                                          5031.12711571215                  None                                          6183.82364721878                  None                                          8952.31975962078                   None                                           10441.7375680915                   None                                           12054.4435931163                   None                                           7957.55789315654                  None                                          15036.1316712316                   None                                           13430.4914212645                  None                                          32427.1596037519                   None                                           63309.9050677925                   None                                       \n", 
9113              "None          44         I           None        N                8426.54623319716                   None                                           10357.9152496503                   None                                            2708.3751705368                  None                                          4091.82359712664                  None                                          5029.86337809029                  None                                          6182.79552045043                  None                                          8979.12144335458                   None                                           10488.2688526334                   None                                           12094.7720286018                   None                                           8018.51779989075                  None                                          15101.1843990883                   None                                           13503.2816173444                  None                                          32502.9389163062                   None                                           63387.6763306952                   None                                       \n", 
9114              "None          45         K           None        N                8599.01176345321                   None                                           10498.7013581079                   None                                           3204.93649737055                  None                                          4436.14046641897                  None                                          5313.74138343704                  None                                          6415.86177652694                  None                                          8546.79665373249                   None                                           9587.16245449134                   None                                           11322.2529042385                   None                                           6797.53838612575                  None                                          13745.1536613763                   None                                           11967.5433300612                  None                                          30890.8603419261                   None                                           61730.6213936947                   None                                       \n", 
9115              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9116              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9117              "None          49         A           None        N                9279.63849130869                   None                                           11063.0654625247                   None                                           4737.11992391463                  None                                          5643.40583860235                  None                                          6356.45614406507                  None                                          7302.87406141381                  None                                          8459.17105047661                   None                                           8761.54554569995                   None                                           10632.2343488142                   None                                           5572.92782399155                  None                                          12102.1714908775                   None                                           10037.6988885228                  None                                          28806.6916858172                   None                                           59579.0348769179                   None                                       \n", 
9118              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9119              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9120              "None          52         V           None        N                8704.45610117774                   None                                           10585.2389163429                   None                                            3477.9549539207                  None                                          4637.22923167743                  None                                          5482.73656118686                  None                                           6556.5108895527                  None                                          8481.06470969555                   None                                           9372.86414918436                   None                                           11141.3782476763                   None                                           6491.79686536093                  None                                          13378.2843939736                   None                                           11544.3205736882                  None                                            30440.62308788                   None                                           61266.7742546508                   None                                       \n", 
9121              "None          53         A           None        N                9497.02860450276                   None                                           11246.0339326126                   None                                           5149.96766581255                  None                                          5994.15475647208                  None                                          6669.81232845336                  None                                          7577.19152075731                  None                                          8516.77431951689                   None                                           8639.36099840319                   None                                           10531.7750336522                   None                                           5378.79193153767                  None                                          11752.8060152439                   None                                           9613.59939949642                  None                                          28334.9153747994                   None                                           59090.2988815445                   None                                       \n", 
9122              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9123              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9124              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9125              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9126              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
9127          ] 
9128          # Check the created w_eff file. 
9129          lines = w_eff_file.readlines() 
9130          for i in range(len(lines)): 
9131              # Test lines starting with # 
9132              if w_eff_result[i][0] == "#": 
9133                  self.assertEqual(w_eff_result[i], lines[i]) 
9134              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
9135              if w_eff_result[i] == lines[i]: 
9136                  self.assertEqual(w_eff_result[i], lines[i]) 
9137              # If the line is not equal each other, make a slower comparison of values. 
9138              else: 
9139                  # Print lines if they don't match. To help find differences. 
9140                  print(w_eff_result[i]) 
9141                  print(lines[i]) 
9142   
9143                  # First test first 62 characters containing spin information 
9144                  self.assertEqual(w_eff_result[i][:62], lines[i][:62]) 
9145   
9146                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
9147                  w_eff_result_s = w_eff_result[i][62:].split()[::2] 
9148                  print(w_eff_result_s ) 
9149                  lines_s = lines[i][62:].split()[::2] 
9150                  print(lines_s) 
9151                  # Loop over the value elements 
9152                  for j in range(len(lines_s)): 
9153                      print(w_eff_result_s[j], lines_s[j]) 
9154                      # Assume a precision to digits. 
9155                      self.assertAlmostEqual(float(w_eff_result_s[j]), float(lines_s[j]), 14) 
9156   
9157          # Close file 
9158          w_eff_file.close() 
9159   
9160   
9161 -    def verify_estimate_r2eff_err_compare_mc(self): 
9162          """Test the user function for estimating R2eff errors from exponential curve fitting, and compare it with Monte-Carlo simulations. 
9163   
9164          This follows Task 7822. 
9165          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
9166   
9167          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
9168          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
9169          """ 
9170   
9171          # Load the data. 
9172          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
9173   
9174          # Set pipe name, bundle and type. 
9175          pipe_name = 'base pipe' 
9176          pipe_bundle = 'relax_disp' 
9177          pipe_type = 'relax_disp' 
9178   
9179          # Create the data pipe. 
9180          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
9181   
9182          file = data_path + '1_setup_r1rho_GUI.py' 
9183          self.interpreter.script(file=file, dir=None) 
9184   
9185          # Deselect all spins. 
9186          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
9187   
9188          # Select one spin. 
9189          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
9190   
9191          # Set the model. 
9192          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
9193   
9194          # Check if intensity errors have already been calculated. 
9195          check_intensity_errors() 
9196   
9197          # Do a grid search. 
9198          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
9199   
9200          # Set algorithm. 
9201          min_algor = 'Newton' 
9202          constraints = True 
9203          if constraints: 
9204              min_options = ('%s'%(min_algor),) 
9205              #min_algor = 'Log barrier' 
9206              min_algor = 'Method of Multipliers' 
9207              scaling_matrix = assemble_scaling_matrix(scaling=True) 
9208   
9209              # Collect spins 
9210              all_spin_ids = [] 
9211              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9212                  all_spin_ids.append(spin_id) 
9213   
9214              spins = spin_ids_to_containers(all_spin_ids[:1]) 
9215   
9216              # Get constraints 
9217              A, b = linear_constraints(spins=spins, scaling_matrix=scaling_matrix[0]) 
9218          else: 
9219              min_options = () 
9220              A, b = None, None 
9221          min_options = () 
9222          sim_boot = 200 
9223          scaling_list = [1.0, 1.0] 
9224   
9225          # Minimise. 
9226          self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints, verbosity=1) 
9227   
9228          # Loop over old err attributes. 
9229          err_attr_list = ['r2eff_err', 'i0_err'] 
9230   
9231          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9232              # Loop over old err attributes. 
9233              for err_attr in err_attr_list: 
9234                  if hasattr(cur_spin, err_attr): 
9235                      delattr(cur_spin, err_attr) 
9236   
9237          # Collect the estimation data from boot. 
9238          my_dic = {} 
9239          param_key_list = [] 
9240          est_keys = [] 
9241          est_key = '-2' 
9242          est_keys.append(est_key) 
9243          spin_id_list = [] 
9244   
9245          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9246              # Add key to dic. 
9247              my_dic[spin_id] = {} 
9248   
9249              # Add key for estimate. 
9250              my_dic[spin_id][est_key] = {} 
9251   
9252              # Add spin key to list. 
9253              spin_id_list.append(spin_id) 
9254   
9255              # Generate spin string. 
9256              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9257   
9258              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9259                  # Generate the param_key. 
9260                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9261   
9262                  # Append key. 
9263                  param_key_list.append(param_key) 
9264   
9265                  # Add key to dic. 
9266                  my_dic[spin_id][est_key][param_key] = {} 
9267   
9268                  values = [] 
9269                  errors = [] 
9270                  times = [] 
9271                  for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
9272                      values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
9273                      errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
9274                      times.append(time) 
9275   
9276                  # Convert to numpy array. 
9277                  values = asarray(values) 
9278                  errors = asarray(errors) 
9279                  times = asarray(times) 
9280   
9281                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
9282                  i0 = getattr(cur_spin, 'i0')[param_key] 
9283   
9284                  R_m_sim_l = [] 
9285                  I0_m_sim_l = [] 
9286                  for j in range(sim_boot): 
9287                      if j in range(0, 100000, 100): 
9288                          print("Simulation %i"%j) 
9289                      # Start minimisation. 
9290   
9291                      # Produce errors 
9292                      I_err = [] 
9293                      for j, error in enumerate(errors): 
9294                          I_error = gauss(values[j], error) 
9295                          I_err.append(I_error) 
9296                      # Convert to numpy array. 
9297                      I_err = asarray(I_err) 
9298   
9299                      x0 = [r2eff, i0] 
9300                      model = Relax_fit_opt(num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
9301   
9302                      # Ref input. 
9303                      #def generic_minimise(func=None, dfunc=None, d2func=None, args=(), x0=None, min_algor=None, min_options=None, func_tol=1e-25, grad_tol=None, maxiter=1e6, A=None, b=None, l=None, u=None, c=None, dc=None, d2c=None, print_flag=0, print_prefix="", full_output=False): 
9304                      # l=l, u=u, c=c, dc=dc, d2c=d2c 
9305                      # l: Lower bound constraint vector (l <= x <= u). 
9306                      # u: Upper bound constraint vector (l <= x <= u). 
9307                      # c: User supplied constraint function. 
9308                      # dc: User supplied constraint gradient function. 
9309                      params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, A=A, b=b, full_output=True, print_flag=0) 
9310   
9311                      R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
9312                      R_m_sim_l.append(R_m_sim_j) 
9313                      I0_m_sim_l.append(I0_m_sim_j) 
9314   
9315                  # Get stats on distribution. 
9316                  sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
9317                  sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
9318                  my_dic[spin_id][est_key][param_key]['r2eff_err'] = sigma_R_sim 
9319                  my_dic[spin_id][est_key][param_key]['i0_err'] = sigma_I0_sim 
9320   
9321          # Estimate R2eff errors. 
9322          self.interpreter.relax_disp.r2eff_err_estimate() 
9323   
9324          est_key = '-1' 
9325          est_keys.append(est_key) 
9326   
9327          # Collect data. 
9328          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9329              # Add key for estimate. 
9330              my_dic[spin_id][est_key] = {} 
9331   
9332              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9333                  # Generate the param_key. 
9334                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9335   
9336                  # Add key to dic. 
9337                  my_dic[spin_id][est_key][param_key] = {} 
9338   
9339                  # Get the value. 
9340                  # Loop over err attributes. 
9341                  for err_attr in err_attr_list: 
9342                      if hasattr(cur_spin, err_attr): 
9343                          get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9344                      else: 
9345                          get_err_attr = 0.0 
9346   
9347                      # Save to dic. 
9348                      my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9349   
9350   
9351          # Make Carlo Simulations number 
9352          mc_number_list = list(range(0, 1000, 250)) 
9353   
9354          sim_attr_list = ['chi2_sim', 'f_count_sim', 'g_count_sim', 'h_count_sim', 'i0_sim', 'iter_sim', 'peak_intensity_sim', 'r2eff_sim', 'select_sim', 'warning_sim'] 
9355   
9356          # Loop over the Monte Carlo simulations: 
9357          for number in mc_number_list: 
9358              # First delete old simulations. 
9359              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9360                  # Loop over old err attributes. 
9361                  for err_attr in err_attr_list: 
9362                      if hasattr(cur_spin, err_attr): 
9363                          delattr(cur_spin, err_attr) 
9364   
9365                  # Loop over the simulated attributes. 
9366                  for sim_attr in sim_attr_list: 
9367                      if hasattr(cur_spin, sim_attr): 
9368                          delattr(cur_spin, sim_attr) 
9369   
9370              self.interpreter.monte_carlo.setup(number=number) 
9371              self.interpreter.monte_carlo.create_data() 
9372              self.interpreter.monte_carlo.initial_values() 
9373              self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints) 
9374              self.interpreter.eliminate() 
9375              self.interpreter.monte_carlo.error_analysis() 
9376   
9377              est_key = '%i'%number 
9378              est_keys.append(est_key) 
9379   
9380              # Collect data. 
9381              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9382                  # Add key for estimate. 
9383                  my_dic[spin_id][est_key] = {} 
9384   
9385                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9386                      # Generate the param_key. 
9387                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9388   
9389                      # Add key to dic. 
9390                      my_dic[spin_id][est_key][param_key] = {} 
9391   
9392                      # Get the value. 
9393                      # Loop over err attributes. 
9394                      for err_attr in err_attr_list: 
9395                          if hasattr(cur_spin, err_attr): 
9396                              get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9397                          else: 
9398                              get_err_attr = 0.0 
9399   
9400                          # Save to dic. 
9401                          my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9402   
9403          # Set what to extract. 
9404          err_attr = err_attr_list[0] 
9405   
9406          # Define list with text. 
9407          text_list = [] 
9408   
9409          # Now loop through the data. 
9410          for spin_id in spin_id_list: 
9411              for est_key in est_keys: 
9412                  # Define list to pickup data. 
9413                  r2eff_err_list = [] 
9414   
9415                  for param_key in param_key_list: 
9416                      # Get the value. 
9417                      r2eff_err = my_dic[spin_id][est_key][param_key][err_attr] 
9418   
9419                      # Add to list. 
9420                      r2eff_err_list.append(r2eff_err) 
9421   
9422                  # Sum the list 
9423                  sum_array = sum(array(r2eff_err_list)) 
9424   
9425                  # Join floats to string. 
9426                  r2eff_err_str = " ".join(format(x, "2.3f") for x in r2eff_err_list) 
9427   
9428                  # Define print string. 
9429                  text = "%8s %s sum= %2.3f" % (est_key, r2eff_err_str, sum_array) 
9430                  text_list.append(text) 
9431   
9432   
9433          # Now print. 
9434          filepath = NamedTemporaryFile(delete=False).name 
9435          # Open the files for testing. 
9436          w_file = open(filepath, 'w') 
9437   
9438          print("Printing the estimated R2eff error as function of estimation from Co-variance and number of Monte-Carlo simulations.") 
9439   
9440          for text in text_list: 
9441              # Print. 
9442              print(text) 
9443   
9444              # Write to file. 
9445              w_file.write(text+"\n") 
9446   
9447          # Close files 
9448          w_file.close() 
9449   
9450          print("Filepath is: %s"%filepath) 
9451          print("Start 'gnuplot' and write:") 
9452          print("set term dumb") 
9453          print("plot '%s' using 1:17 title 'R2eff error as function of MC number' w linespoints "%filepath) 
9454   
9455   
9456 -    def verify_r1rho_kjaergaard_missing_r1(self, models=None, result_dir_name=None, r2eff_estimate=None): 
9457          """Verification of test_r1rho_kjaergaard_missing_r1.""" 
9458   
9459          # Check the kex value of residue 52 
9460          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
9461   
9462          # Print results for each model. 
9463          print("\n\n################") 
9464          print("Printing results") 
9465          print("################\n") 
9466          for model in models: 
9467              # Skip R2eff model. 
9468              if model == MODEL_R2EFF: 
9469                  continue 
9470   
9471              # Switch to pipe. 
9472              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9473              print("\nModel: %s" % (model)) 
9474   
9475              # Loop over the spins. 
9476              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9477                  # Generate spin string. 
9478                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9479   
9480                  # Loop over the parameters. 
9481                  print("Optimised parameters for spin: %s" % (spin_string)) 
9482                  for param in cur_spin.params + ['chi2']: 
9483                      # Get the value. 
9484                      if param in ['r1', 'r2']: 
9485                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
9486                              # Generate the R20 key. 
9487                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
9488   
9489                              # Get the value. 
9490                              value = getattr(cur_spin, param)[r20_key] 
9491   
9492                              # Print value. 
9493                              print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9494   
9495                              # Compare values. 
9496                              if spin_id == ':52@N': 
9497                                  if param == 'r1': 
9498                                      if model == MODEL_NOREX: 
9499                                          if r2eff_estimate == 'direct': 
9500                                              self.assertAlmostEqual(value, 1.46138805) 
9501                                          elif r2eff_estimate == 'MC2000': 
9502                                              self.assertAlmostEqual(value, 1.46328102) 
9503                                          elif r2eff_estimate == 'chi2_pyt': 
9504                                              self.assertAlmostEqual(value, 1.43820629) 
9505                                      elif model == MODEL_DPL94: 
9506                                          if r2eff_estimate == 'direct': 
9507                                              self.assertAlmostEqual(value, 1.44845742) 
9508                                          elif r2eff_estimate == 'MC2000': 
9509                                              self.assertAlmostEqual(value, 1.45019848) 
9510                                          elif r2eff_estimate == 'chi2_pyt': 
9511                                              self.assertAlmostEqual(value, 1.44666512) 
9512                                      elif model == MODEL_TP02: 
9513                                          if r2eff_estimate == 'direct': 
9514                                              self.assertAlmostEqual(value, 1.54354392) 
9515                                          elif r2eff_estimate == 'MC2000': 
9516                                              self.assertAlmostEqual(value, 1.54352369) 
9517                                          elif r2eff_estimate == 'chi2_pyt': 
9518                                              self.assertAlmostEqual(value, 1.55964020) 
9519                                      elif model == MODEL_TAP03: 
9520                                          if r2eff_estimate == 'direct': 
9521                                              self.assertAlmostEqual(value, 1.54356410) 
9522                                          elif r2eff_estimate == 'MC2000': 
9523                                              self.assertAlmostEqual(value, 1.54354367) 
9524                                          elif r2eff_estimate == 'chi2_pyt': 
9525                                              self.assertAlmostEqual(value, 1.55967157) 
9526                                      elif model == MODEL_MP05: 
9527                                          if r2eff_estimate == 'direct': 
9528                                              self.assertAlmostEqual(value, 1.54356416) 
9529                                          elif r2eff_estimate == 'MC2000': 
9530                                              self.assertAlmostEqual(value, 1.54354372) 
9531                                          elif r2eff_estimate == 'chi2_pyt': 
9532                                              self.assertAlmostEqual(value, 1.55967163) 
9533                                      elif model == MODEL_NS_R1RHO_2SITE: 
9534                                          if r2eff_estimate == 'direct': 
9535                                              self.assertAlmostEqual(value, 1.41359221, 5) 
9536                                          elif r2eff_estimate == 'MC2000': 
9537                                              self.assertAlmostEqual(value, 1.41321968, 5) 
9538                                          elif r2eff_estimate == 'chi2_pyt': 
9539                                              self.assertAlmostEqual(value, 1.36303129, 5) 
9540   
9541                                  elif param == 'r2': 
9542                                      if model == MODEL_NOREX: 
9543                                          if r2eff_estimate == 'direct': 
9544                                              self.assertAlmostEqual(value, 11.48392439) 
9545                                          elif r2eff_estimate == 'MC2000': 
9546                                              self.assertAlmostEqual(value, 11.48040934) 
9547                                          elif r2eff_estimate == 'chi2_pyt': 
9548                                              self.assertAlmostEqual(value, 11.47224488) 
9549                                      elif model == MODEL_DPL94: 
9550                                          if r2eff_estimate == 'direct': 
9551                                              self.assertAlmostEqual(value, 10.15688372, 6) 
9552                                          elif r2eff_estimate == 'MC2000': 
9553                                              self.assertAlmostEqual(value, 10.16304887, 6) 
9554                                          elif r2eff_estimate == 'chi2_pyt': 
9555                                              self.assertAlmostEqual(value, 9.20037797, 6) 
9556                                      elif model == MODEL_TP02: 
9557                                          if r2eff_estimate == 'direct': 
9558                                              self.assertAlmostEqual(value, 9.72654896, 6) 
9559                                          elif r2eff_estimate == 'MC2000': 
9560                                              self.assertAlmostEqual(value, 9.72772726, 6) 
9561                                          elif r2eff_estimate == 'chi2_pyt': 
9562                                              self.assertAlmostEqual(value, 9.53948340, 6) 
9563                                      elif model == MODEL_TAP03: 
9564                                          if r2eff_estimate == 'direct': 
9565                                              self.assertAlmostEqual(value, 9.72641887, 6) 
9566                                          elif r2eff_estimate == 'MC2000': 
9567                                              self.assertAlmostEqual(value, 9.72759374, 6) 
9568                                          elif r2eff_estimate == 'chi2_pyt': 
9569                                              self.assertAlmostEqual(value, 9.53926913, 6) 
9570                                      elif model == MODEL_MP05: 
9571                                          if r2eff_estimate == 'direct': 
9572                                              self.assertAlmostEqual(value, 9.72641723, 6) 
9573                                          elif r2eff_estimate == 'MC2000': 
9574                                              self.assertAlmostEqual(value, 9.72759220, 6) 
9575                                          elif r2eff_estimate == 'chi2_pyt': 
9576                                              self.assertAlmostEqual(value, 9.53926778, 6) 
9577                                      elif model == MODEL_NS_R1RHO_2SITE: 
9578                                          if r2eff_estimate == 'direct': 
9579                                              self.assertAlmostEqual(value, 9.34531535, 5) 
9580                                          elif r2eff_estimate == 'MC2000': 
9581                                              self.assertAlmostEqual(value, 9.34602793, 5) 
9582                                          elif r2eff_estimate == 'chi2_pyt': 
9583                                              self.assertAlmostEqual(value, 9.17631409, 5) 
9584   
9585                      # For all other parameters. 
9586                      else: 
9587                          # Get the value. 
9588                          value = getattr(cur_spin, param) 
9589   
9590                          # Print value. 
9591                          print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9592   
9593                          # Compare values. 
9594                          if spin_id == ':52@N': 
9595                              if param == 'phi_ex': 
9596                                  if model == MODEL_DPL94: 
9597                                      if r2eff_estimate == 'direct': 
9598                                          self.assertAlmostEqual(value, 0.07599563) 
9599                                      elif r2eff_estimate == 'MC2000': 
9600                                          self.assertAlmostEqual(value, 0.07561937) 
9601                                      elif r2eff_estimate == 'chi2_pyt': 
9602                                          self.assertAlmostEqual(value, 0.12946061) 
9603   
9604                              elif param == 'pA': 
9605                                  if model == MODEL_TP02: 
9606                                      if r2eff_estimate == 'direct': 
9607                                          self.assertAlmostEqual(value, 0.88827040) 
9608                                      elif r2eff_estimate == 'MC2000': 
9609                                          self.assertAlmostEqual(value, 0.88807487) 
9610                                      elif r2eff_estimate == 'chi2_pyt': 
9611                                          self.assertAlmostEqual(value, 0.87746233) 
9612                                  elif model == MODEL_TAP03: 
9613                                      if r2eff_estimate == 'direct': 
9614                                          self.assertAlmostEqual(value, 0.88828922) 
9615                                      elif r2eff_estimate == 'MC2000': 
9616                                          self.assertAlmostEqual(value, 0.88809318) 
9617                                      elif r2eff_estimate == 'chi2_pyt': 
9618                                          self.assertAlmostEqual(value, 0.87747558) 
9619                                  elif model == MODEL_MP05: 
9620                                      if r2eff_estimate == 'direct': 
9621                                          self.assertAlmostEqual(value, 0.88828924, 6) 
9622                                      elif r2eff_estimate == 'MC2000': 
9623                                          self.assertAlmostEqual(value, 0.88809321) 
9624                                      elif r2eff_estimate == 'chi2_pyt': 
9625                                          self.assertAlmostEqual(value, 0.87747562) 
9626                                  elif model == MODEL_NS_R1RHO_2SITE: 
9627                                      if r2eff_estimate == 'direct': 
9628                                          self.assertAlmostEqual(value, 0.94504369, 6) 
9629                                      elif r2eff_estimate == 'MC2000': 
9630                                          self.assertAlmostEqual(value, 0.94496541, 6) 
9631                                      elif r2eff_estimate == 'chi2_pyt': 
9632                                          self.assertAlmostEqual(value, 0.92084707, 6) 
9633   
9634                              elif param == 'dw': 
9635                                  if model == MODEL_TP02: 
9636                                      if r2eff_estimate == 'direct': 
9637                                          self.assertAlmostEqual(value, 1.08875840, 6) 
9638                                      elif r2eff_estimate == 'MC2000': 
9639                                          self.assertAlmostEqual(value, 1.08765638, 6) 
9640                                      elif r2eff_estimate == 'chi2_pyt': 
9641                                          self.assertAlmostEqual(value, 1.09753230, 6) 
9642                                  elif model == MODEL_TAP03: 
9643                                      if r2eff_estimate == 'direct': 
9644                                          self.assertAlmostEqual(value, 1.08837238, 6) 
9645                                      elif r2eff_estimate == 'MC2000': 
9646                                          self.assertAlmostEqual(value, 1.08726698, 6) 
9647                                      elif r2eff_estimate == 'chi2_pyt': 
9648                                          self.assertAlmostEqual(value, 1.09708821, 6) 
9649                                  elif model == MODEL_MP05: 
9650                                      if r2eff_estimate == 'direct': 
9651                                          self.assertAlmostEqual(value, 1.08837241, 6) 
9652                                      elif r2eff_estimate == 'MC2000': 
9653                                          self.assertAlmostEqual(value, 1.08726706, 6) 
9654                                      elif r2eff_estimate == 'chi2_pyt': 
9655                                          self.assertAlmostEqual(value, 1.09708832, 6) 
9656                                  elif model == MODEL_NS_R1RHO_2SITE: 
9657                                      if r2eff_estimate == 'direct': 
9658                                          self.assertAlmostEqual(value, 1.56001812, 5) 
9659                                      elif r2eff_estimate == 'MC2000': 
9660                                          self.assertAlmostEqual(value, 1.55833321, 5) 
9661                                      elif r2eff_estimate == 'chi2_pyt': 
9662                                          self.assertAlmostEqual(value, 1.36406712, 5) 
9663   
9664                              elif param == 'kex': 
9665                                  if model == MODEL_DPL94: 
9666                                      if r2eff_estimate == 'direct': 
9667                                          self.assertAlmostEqual(value/1e5, 4460.43711569/1e5, 7) 
9668                                      elif r2eff_estimate == 'MC2000': 
9669                                          self.assertAlmostEqual(value/1e5, 4419.03917195/1e5, 7) 
9670                                      elif r2eff_estimate == 'chi2_pyt': 
9671                                          self.assertAlmostEqual(value/1e5, 6790.22736344/1e5, 7) 
9672                                  elif model == MODEL_TP02: 
9673                                      if r2eff_estimate == 'direct': 
9674                                          self.assertAlmostEqual(value/1e5, 4921.28602757/1e5, 7) 
9675                                      elif r2eff_estimate == 'MC2000': 
9676                                          self.assertAlmostEqual(value/1e5, 4904.70144883/1e5, 7) 
9677                                      elif r2eff_estimate == 'chi2_pyt': 
9678                                          self.assertAlmostEqual(value/1e5, 5146.20306591/1e5, 7) 
9679                                  elif model == MODEL_TAP03: 
9680                                      if r2eff_estimate == 'direct': 
9681                                          self.assertAlmostEqual(value/1e5, 4926.42963491/1e5, 7) 
9682                                      elif r2eff_estimate == 'MC2000': 
9683                                          self.assertAlmostEqual(value/1e5, 4909.86877150/1e5, 7) 
9684                                      elif r2eff_estimate == 'chi2_pyt': 
9685                                          self.assertAlmostEqual(value/1e5, 5152.51105814/1e5, 7) 
9686                                  elif model == MODEL_MP05: 
9687                                      if r2eff_estimate == 'direct': 
9688                                          self.assertAlmostEqual(value/1e5, 4926.44236315/1e5, 7) 
9689                                      elif r2eff_estimate == 'MC2000': 
9690                                          self.assertAlmostEqual(value/1e5, 4909.88110195/1e5, 7) 
9691                                      elif r2eff_estimate == 'chi2_pyt': 
9692                                          self.assertAlmostEqual(value/1e5, 5152.52097111/1e5, 7) 
9693                                  elif model == MODEL_NS_R1RHO_2SITE: 
9694                                      if r2eff_estimate == 'direct': 
9695                                          self.assertAlmostEqual(value/1e5, 5628.66061488/1e5, 6) 
9696                                      elif r2eff_estimate == 'MC2000': 
9697                                          self.assertAlmostEqual(value/1e5, 5610.20221435/1e5, 6) 
9698                                      elif r2eff_estimate == 'chi2_pyt': 
9699                                          self.assertAlmostEqual(value/1e5, 5643.34067090/1e5, 6) 
9700   
9701                              elif param == 'chi2': 
9702                                  if model == MODEL_NOREX: 
9703                                      if r2eff_estimate == 'direct': 
9704                                          self.assertAlmostEqual(value, 848.42016907, 5) 
9705                                      elif r2eff_estimate == 'MC2000': 
9706                                          self.assertAlmostEqual(value, 3363.95829122, 5) 
9707                                      elif r2eff_estimate == 'chi2_pyt': 
9708                                          self.assertAlmostEqual(value, 5976.49946726, 5) 
9709                                  elif model == MODEL_DPL94: 
9710                                      if r2eff_estimate == 'direct': 
9711                                          self.assertAlmostEqual(value, 179.47041241) 
9712                                      elif r2eff_estimate == 'MC2000': 
9713                                          self.assertAlmostEqual(value, 710.24767560) 
9714                                      elif r2eff_estimate == 'chi2_pyt': 
9715                                          self.assertAlmostEqual(value, 612.72616697, 5) 
9716                                  elif model == MODEL_TP02: 
9717                                      if r2eff_estimate == 'direct': 
9718                                          self.assertAlmostEqual(value, 29.33882530, 6) 
9719                                      elif r2eff_estimate == 'MC2000': 
9720                                          self.assertAlmostEqual(value, 114.47142772, 6) 
9721                                      elif r2eff_estimate == 'chi2_pyt': 
9722                                          self.assertAlmostEqual(value, 250.50838162, 5) 
9723                                  elif model == MODEL_TAP03: 
9724                                      if r2eff_estimate == 'direct': 
9725                                          self.assertAlmostEqual(value, 29.29050673, 6) 
9726                                      elif r2eff_estimate == 'MC2000': 
9727                                          self.assertAlmostEqual(value, 114.27987534) 
9728                                      elif r2eff_estimate == 'chi2_pyt': 
9729                                          self.assertAlmostEqual(value, 250.04050719, 5) 
9730                                  elif model == MODEL_MP05: 
9731                                      if r2eff_estimate == 'direct': 
9732                                          self.assertAlmostEqual(value, 29.29054301, 6) 
9733                                      elif r2eff_estimate == 'MC2000': 
9734                                          self.assertAlmostEqual(value, 114.28002272) 
9735                                      elif r2eff_estimate == 'chi2_pyt': 
9736                                          self.assertAlmostEqual(value, 250.04077478, 5) 
9737                                  elif model == MODEL_NS_R1RHO_2SITE: 
9738                                      if r2eff_estimate == 'direct': 
9739                                          self.assertAlmostEqual(value, 34.44010543, 6) 
9740                                      elif r2eff_estimate == 'MC2000': 
9741                                          self.assertAlmostEqual(value, 134.14368365) 
9742                                      elif r2eff_estimate == 'chi2_pyt': 
9743                                          self.assertAlmostEqual(value, 278.55121388, 5) 
9744   
9745   
9746          # Print the final pipe. 
9747          model = 'final' 
9748          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9749          print("\nFinal pipe") 
9750   
9751          # Loop over the spins. 
9752          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9753              # Generate spin string. 
9754              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9755   
9756              # Loop over the parameters. 
9757              print("Optimised model for spin: %s" % (spin_string)) 
9758              param = 'model' 
9759   
9760              # Get the value. 
9761              value = getattr(cur_spin, param) 
9762              print("%-10s %-6s %-6s %6s" % ("Parameter:", param, "Value:", value)) 
9763   
9764   
9765          ### Now check some of the written out files. 
9766          file_names = ['r1rho_prime', 'r1'] 
9767   
9768          for file_name_i in file_names: 
9769   
9770              # Make the file name. 
9771              file_name = "%s.out" % file_name_i 
9772   
9773              # Get the file path. 
9774              file_path = get_file_path(file_name, result_dir_name + sep + model) 
9775   
9776              # Test the file exists. 
9777              print("Testing file access to: %s"%file_path) 
9778              self.assert_(access(file_path, F_OK)) 
9779   
9780              # Now open, and compare content, line by line. 
9781              file_prod = open(file_path) 
9782              lines_prod = file_prod.readlines() 
9783              file_prod.close() 
9784   
9785              # Loop over the lines. 
9786              for i, line in enumerate(lines_prod): 
9787                  # Make the string test 
9788                  line_split = line.split() 
9789   
9790                  # Continue for comment lines. 
9791                  if line_split[0] == "#": 
9792                      print(line), 
9793                      continue 
9794   
9795                  # Assign the split of the line. 
9796                  mol_name, res_num, res_name, spin_num, spin_name, val, sd_error = line_split 
9797                  print(mol_name, res_num, res_name, spin_num, spin_name, val, sd_error) 
9798   
9799                  if res_num == '52': 
9800                      # Assert that the value is not None. 
9801                      self.assertNotEqual(val, 'None') 
9802